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• Converting linear colors to SRGB shows banding in FFmpeg

  - by user1863947

  When I convert an EXR file sequence with x264 using FFmpeg and convert the colorspace from linear to SRGB (with gamma 0.45454545) I get some heavy banding issues (most visible on a dark gradient). Here is the ffmpeg command I use: C:/ffmpeg.exe -y -i C:/seq_v001.%04d.exr -vf lutrgb=r=gammaval(0.45454545):g=gammaval(0.45454545):b=gammaval(0.45454545) -vcodec libx264 -pix_fmt yuv420p -preset slow -crf 18 -r 25 C:/out.mov Here is the output: ffmpeg version N-47062-g26c531c Copyright (c) 2000-2012 the FFmpeg developers built on Nov 25 2012 12:25:21 with gcc 4.7.2 (GCC) configuration: --enable-gpl --enable-version3 --disable-pthreads --enable-runtime-cpudetect --enable-avisynth --enable-bzlib --enable-frei0r --enable-libass --enable-libopencore-amrnb --enable-libopencore-amrwb --enable-libfreetype --enable-libgsm --enable-libmp3lame --enable-libnut --enable-libopenjpeg --enable-libopus --enable-librtmp --enable-libschroedinger --enable-libspeex --enable-libtheora --enable-libutvideo --enable-libvo-aacenc --enable-libvo-amrwbenc --enable-libvorbis --enable-libvpx --enable-libx264 --enable-libxavs --enable-libxvid --enable-zlib libavutil 52. 9.100 / 52. 9.100 libavcodec 54. 77.100 / 54. 77.100 libavformat 54. 37.100 / 54. 37.100 libavdevice 54. 3.100 / 54. 3.100 libavfilter 3. 23.102 / 3. 23.102 libswscale 2. 1.102 / 2. 1.102 libswresample 0. 17.101 / 0. 17.101 libpostproc 52. 2.100 / 52. 2.100 Input #0, image2, from 'C:/seq_v001.%04d.exr': Duration: 00:00:09.60, start: 0.000000, bitrate: N/A Stream #0:0: Video: exr, rgb48le, 960x540 [SAR 1:1 DAR 16:9], 25 fps, 25 tbr, 25 tbn, 25 tbc [libx264 @ 0000000004d11540] using SAR=1/1 [libx264 @ 0000000004d11540] using cpu capabilities: MMX2 SSE2Fast SSSE3 FastShuffle SSE4.2 [libx264 @ 0000000004d11540] profile High, level 3.1 [libx264 @ 0000000004d11540] 264 - core 128 r2216 198a7ea - H.264/MPEG-4 AVC codec - Copyleft 2003-2012 - http://www.videolan.org/x264.html - options: cabac=1 ref=5 deblock=1:0:0 analyse=0x3:0x113 me=umh subme=8 psy=1 psy_rd=1.00:0.00 mixed_ref=1 me_range=16 chroma_me=1 trellis=1 8x8dct=1 cqm=0 deadzone=21,11 fast_pskip=1 chroma_qp_offset=-2 threads=18 lookahead_threads=3 sliced_threads=0 nr=0 decimate=1 interlaced=0 bluray_compat=0 constrained_intra=0 bframes=3 b_pyramid=2 b_adapt=2 b_bias=0 direct=3 weightb=1 open_gop=0 weightp=2 keyint=250 keyint_min=25 scenecut=40 intra_refresh=0 rc_lookahead=50 rc=crf mbtree=1 crf=18.0 qcomp=0.60 qpmin=0 qpmax=69 qpstep=4 ip_ratio=1.40 aq=1:1.00 Output #0, mov, to 'C:/out.mov': Metadata: encoder : Lavf54.37.100 Stream #0:0: Video: h264 (avc1 / 0x31637661), yuv420p, 960x540 [SAR 1:1 DAR 16:9], q=-1--1, 12800 tbn, 25 tbc Stream mapping: Stream #0:0 -> #0:0 (exr -> libx264) Press [q] to stop, [?] for help [exr @ 000000000dff8c40] Found more than one compression attribute [exr @ 000000000dff90c0] Found more than one compression attribute [exr @ 000000000dff9520] Found more than one compression attribute [exr @ 000000000dff9960] Found more than one compression attribute [exr @ 000000000dff9dc0] Found more than one compression attribute [exr @ 000000000dffa200] Found more than one compression attribute [exr @ 000000000dffa660] Found more than one compression attribute [exr @ 000000000dffaaa0] Found more than one compression attribute [exr @ 000000000dffaf00] Found more than one compression attribute [exr @ 000000000dffb340] Found more than one compression attribute [exr @ 000000000dffb7a0] Found more than one compression attribute [exr @ 000000000dffbbe0] Found more than one compression attribute [exr @ 000000000dffc040] Found more than one compression attribute [exr @ 000000000dff8c40] Found more than one compression attribute [exr @ 000000000dff90c0] Found more than one compression attribute frame= 16 fps=0.0 q=0.0 size= 0kB time=00:00:00.00 bitrate= 0.0kbits/s Found more than one compression attribute [exr @ 000000000dff9960] Found more than one compression attribute [exr @ 000000000dff9dc0] Found more than one compression attribute [exr @ 000000000dffa200] Found more than one compression attribute [exr @ 000000000dffa660] Found more than one compression attribute [exr @ 000000000dffaaa0] Found more than one compression attribute [exr @ 000000000dffaf00] Found more than one compression attribute [exr @ 000000000dffb340] Found more than one compression attribute [exr @ 000000000dffb7a0] Found more than one compression attribute [exr @ 000000000dffbbe0] Found more than one compression attribute [exr @ 000000000dffc040] Found more than one compression attribute [exr @ 000000000dff8c40] Found more than one compression attribute [exr @ 000000000dff90c0] Found more than one compression attribute [exr @ 000000000dff9520] Found more than one compression attribute [exr @ 000000000dff9960] Found more than one compression attribute [exr @ 000000000dff9dc0] Found more than one compression attribute [exr @ 000000000dffa200] Found more than one compression attribute [exr @ 000000000dffa660] Found more than one compression attribute frame= 34 fps= 33 q=0.0 size= 0kB time=00:00:00.00 bitrate= 0.0kbits/s Found more than one compression attribute [exr @ 000000000dffaf00] Found more than one compression attribute [exr @ 000000000dffb340] Found more than one compression attribute [exr @ 000000000dffb7a0] Found more than one compression attribute [exr @ 000000000dffbbe0] Found more than one compression attribute [exr @ 000000000dffc040] Found more than one compression attribute [exr @ 000000000dff8c40] Found more than one compression attribute [exr @ 000000000dff90c0] Found more than one compression attribute [exr @ 000000000dff9520] Found more than one compression attribute [exr @ 000000000dff9960] Found more than one compression attribute [exr @ 000000000dff9dc0] Found more than one compression attribute [exr @ 000000000dffa200] Found more than one compression attribute [exr @ 000000000dffa660] Found more than one compression attribute [exr @ 000000000dffaaa0] Found more than one compression attribute [exr @ 000000000dffaf00] Found more than one compression attribute [exr @ 000000000dffb340] Found more than one compression attribute [exr @ 000000000dffb7a0] Found more than one compression attribute [exr @ 000000000dffbbe0] Found more than one compression attribute frame= 52 fps= 34 q=0.0 size= 0kB time=00:00:00.00 bitrate= 0.0kbits/s Found more than one compression attribute [exr @ 000000000dff8c40] Found more than one compression attribute [exr @ 000000000dff90c0] Found more than one compression attribute [exr @ 000000000dff9520] Found more than one compression attribute [exr @ 000000000dff9960] Found more than one compression attribute [exr @ 000000000dff9dc0] Found more than one compression attribute [exr @ 000000000dffa200] Found more than one compression attribute [exr @ 000000000dffa660] Found more than one compression attribute [exr @ 000000000dffaaa0] Found more than one compression attribute [exr @ 000000000dffaf00] Found more than one compression attribute [exr @ 000000000dffb340] Found more than one compression attribute [exr @ 000000000dffb7a0] Found more than one compression attribute [exr @ 000000000dffbbe0] Found more than one compression attribute [exr @ 000000000dffc040] Found more than one compression attribute [exr @ 000000000dff8c40] Found more than one compression attribute [exr @ 000000000dff90c0] Found more than one compression attribute frame= 68 fps= 34 q=0.0 size= 0kB time=00:00:00.00 bitrate= 0.0kbits/s Found more than one compression attribute [exr @ 000000000dff9960] Found more than one compression attribute [exr @ 000000000dff9dc0] Found more than one compression attribute [exr @ 000000000dffa200] Found more than one compression attribute [exr @ 000000000dffa660] Found more than one compression attribute [exr @ 000000000dffaaa0] Found more than one compression attribute [exr @ 000000000dffaf00] Found more than one compression attribute [exr @ 000000000dffb340] Found more than one compression attribute [exr @ 000000000dffb7a0] Found more than one compression attribute [exr @ 000000000dffbbe0] Found more than one compression attribute [exr @ 000000000dffc040] Found more than one compression attribute [exr @ 000000000dff8c40] Found more than one compression attribute [exr @ 000000000dff90c0] Found more than one compression attribute [exr @ 000000000dff9520] Found more than one compression attribute [exr @ 000000000dff9960] Found more than one compression attribute [exr @ 000000000dff9dc0] Found more than one compression attribute [exr @ 000000000dffa200] Found more than one compression attribute frame= 85 fps= 33 q=23.0 size= 47kB time=00:00:00.44 bitrate= 867.5kbits/s Found more than one compression attribute [exr @ 000000000dffaaa0] Found more than one compression attribute [exr @ 000000000dffaf00] Found more than one compression attribute [exr @ 000000000dffb340] Found more than one compression attribute [exr @ 000000000dffb7a0] Found more than one compression attribute [exr @ 000000000dffbbe0] Found more than one compression attribute [exr @ 000000000dffc040] Found more than one compression attribute [exr @ 000000000dff8c40] Found more than one compression attribute [exr @ 000000000dff90c0] Found more than one compression attribute [exr @ 000000000dff9520] Found more than one compression attribute [exr @ 000000000dff9960] Found more than one compression attribute [exr @ 000000000dff9dc0] Found more than one compression attribute [exr @ 000000000dffa200] Found more than one compression attribute [exr @ 000000000dffa660] Found more than one compression attribute [exr @ 000000000dffaaa0] Found more than one compression attribute [exr @ 000000000dffaf00] Found more than one compression attribute [exr @ 000000000dffb340] Found more than one compression attribute [exr @ 000000000dffb7a0] Found more than one compression attribute [exr @ 000000000dffbbe0] Found more than one compression attribute frame= 104 fps= 34 q=23.0 size= 94kB time=00:00:01.20 bitrate= 640.3kbits/s Found more than one compression attribute [exr @ 000000000dff8c40] Found more than one compression attribute [exr @ 000000000dff90c0] Found more than one compression attribute [exr @ 000000000dff9520] Found more than one compression attribute [exr @ 000000000dff9960] Found more than one compression attribute [exr @ 000000000dff9dc0] Found more than one compression attribute [exr @ 000000000dffa200] Found more than one compression attribute [exr @ 000000000dffa660] Found more than one compression attribute [exr @ 000000000dffaaa0] Found more than one compression attribute [exr @ 000000000dffaf00] Found more than one compression attribute [exr @ 000000000dffb340] Found more than one compression attribute [exr @ 000000000dffb7a0] Found more than one compression attribute [exr @ 000000000dffbbe0] Found more than one compression attribute [exr @ 000000000dffc040] Found more than one compression attribute [exr @ 000000000dff8c40] Found more than one compression attribute [exr @ 000000000dff90c0] Found more than one compression attribute [exr @ 000000000dff9520] Found more than one compression attribute frame= 121 fps= 34 q=23.0 size= 133kB time=00:00:01.88 bitrate= 577.8kbits/s Found more than one compression attribute [exr @ 000000000dff9dc0] Found more than one compression attribute [exr @ 000000000dffa200] Found more than one compression attribute [exr @ 000000000dffa660] Found more than one compression attribute [exr @ 000000000dffaaa0] Found more than one compression attribute [exr @ 000000000dffaf00] Found more than one compression attribute [exr @ 000000000dffb340] Found more than one compression attribute [exr @ 000000000dffb7a0] Found more than one compression attribute [exr @ 000000000dffbbe0] Found more than one compression attribute [exr @ 000000000dffc040] Found more than one compression attribute [exr @ 000000000dff8c40] Found more than one compression attribute [exr @ 000000000dff90c0] Found more than one compression attribute [exr @ 000000000dff9520] Found more than one compression attribute [exr @ 000000000dff9960] Found more than one compression attribute [exr @ 000000000dff9dc0] Found more than one compression attribute [exr @ 000000000dffa200] Found more than one compression attribute [exr @ 000000000dffa660] Found more than one compression attribute [exr @ 000000000dffaaa0] Found more than one compression attribute frame= 139 fps= 34 q=23.0 size= 172kB time=00:00:02.60 bitrate= 543.4kbits/s Found more than one compression attribute [exr @ 000000000dffb340] Found more than one compression attribute [exr @ 000000000dffb7a0] Found more than one compression attribute [exr @ 000000000dffbbe0] Found more than one compression attribute [exr @ 000000000dffc040] Found more than one compression attribute [exr @ 000000000dff8c40] Found more than one compression attribute [exr @ 000000000dff90c0] Found more than one compression attribute [exr @ 000000000dff9520] Found more than one compression attribute [exr @ 000000000dff9960] Found more than one compression attribute [exr @ 000000000dff9dc0] Found more than one compression attribute [exr @ 000000000dffa200] Found more than one compression attribute [exr @ 000000000dffa660] Found more than one compression attribute [exr @ 000000000dffaaa0] Found more than one compression attribute [exr @ 000000000dffaf00] Found more than one compression attribute [exr @ 000000000dffb340] Found more than one compression attribute [exr @ 000000000dffb7a0] Found more than one compression attribute [exr @ 000000000dffbbe0] Found more than one compression attribute [exr @ 000000000dffc040] Found more than one compression attribute frame= 157 fps= 34 q=23.0 size= 213kB time=00:00:03.32 bitrate= 525.6kbits/s Found more than one compression attribute [exr @ 000000000dff90c0] Found more than one compression attribute [exr @ 000000000dff9520] Found more than one compression attribute [exr @ 000000000dff9960] Found more than one compression attribute [exr @ 000000000dff9dc0] Found more than one compression attribute [exr @ 000000000dffa200] Found more than one compression attribute [exr @ 000000000dffa660] Found more than one compression attribute [exr @ 000000000dffaaa0] Found more than one compression attribute [exr @ 000000000dffaf00] Found more than one compression attribute [exr @ 000000000dffb340] Found more than one compression attribute [exr @ 000000000dffb7a0] Found more than one compression attribute [exr @ 000000000dffbbe0] Found more than one compression attribute [exr @ 000000000dffc040] Found more than one compression attribute [exr @ 000000000dff8c40] Found more than one compression attribute [exr @ 000000000dff90c0] Found more than one compression attribute [exr @ 000000000dff9520] Found more than one compression attribute [exr @ 000000000dff9960] Found more than one compression attribute [exr @ 000000000dff9dc0] Found more than one compression attribute frame= 175 fps= 34 q=23.0 size= 254kB time=00:00:04.04 bitrate= 516.0kbits/s Found more than one compression attribute [exr @ 000000000dffa660] Found more than one compression attribute [exr @ 000000000dffaaa0] Found more than one compression attribute [exr @ 000000000dffaf00] Found more than one compression attribute [exr @ 000000000dffb340] Found more than one compression attribute [exr @ 000000000dffb7a0] Found more than one compression attribute [exr @ 000000000dffbbe0] Found more than one compression attribute [exr @ 000000000dffc040] Found more than one compression attribute [exr @ 000000000dff8c40] Found more than one compression attribute [exr @ 000000000dff90c0] Found more than one compression attribute [exr @ 000000000dff9520] Found more than one compression attribute [exr @ 000000000dff9960] Found more than one compression attribute [exr @ 000000000dff9dc0] Found more than one compression attribute [exr @ 000000000dffa200] Found more than one compression attribute [exr @ 000000000dffa660] Found more than one compression attribute [exr @ 000000000dffaaa0] Found more than one compression attribute [exr @ 000000000dffaf00] Found more than one compression attribute [exr @ 000000000dffb340] Found more than one compression attribute frame= 193 fps= 35 q=23.0 size= 287kB time=00:00:04.76 bitrate= 494.6kbits/s Found more than one compression attribute [exr @ 000000000dffbbe0] Found more than one compression attribute [exr @ 000000000dffc040] Found more than one compression attribute [exr @ 000000000dff8c40] Found more than one compression attribute [exr @ 000000000dff90c0] Found more than one compression attribute [exr @ 000000000dff9520] Found more than one compression attribute [exr @ 000000000dff9960] Found more than one compression attribute [exr @ 000000000dff9dc0] Found more than one compression attribute [exr @ 000000000dffa200] Found more than one compression attribute [exr @ 000000000dffa660] Found more than one compression attribute [exr @ 000000000dffaaa0] Found more than one compression attribute [exr @ 000000000dffaf00] Found more than one compression attribute [exr @ 000000000dffb340] Found more than one compression attribute [exr @ 000000000dffb7a0] Found more than one compression attribute [exr @ 000000000dffbbe0] Found more than one compression attribute [exr @ 000000000dffc040] Found more than one compression attribute [exr @ 000000000dff8c40] Found more than one compression attribute [exr @ 000000000dff90c0] Found more than one compression attribute frame= 211 fps= 35 q=23.0 size= 332kB time=00:00:05.48 bitrate= 496.4kbits/s Found more than one compression attribute [exr @ 000000000dff9960] Found more than one compression attribute [exr @ 000000000dff9dc0] Found more than one compression attribute [exr @ 000000000dffa200] Found more than one compression attribute [exr @ 000000000dffa660] Found more than one compression attribute [exr @ 000000000dffaaa0] Found more than one compression attribute [exr @ 000000000dffaf00] Found more than one compression attribute [exr @ 000000000dffb340] Found more than one compression attribute [exr @ 000000000dffb7a0] Found more than one compression attribute [exr @ 000000000dffbbe0] Found more than one compression attribute [exr @ 000000000dffc040] Found more than one compression attribute [exr @ 000000000dff8c40] Found more than one compression attribute [exr @ 000000000dff90c0] Found more than one compression attribute [exr @ 000000000dff9520] Found more than one compression attribute [exr @ 000000000dff9960] Found more than one compression attribute [exr @ 000000000dff9dc0] Found more than one compression attribute [exr @ 000000000dffa200] Found more than one compression attribute frame= 228 fps= 34 q=23.0 size= 421kB time=00:00:06.16 bitrate= 559.8kbits/s frame= 240 fps= 32 q=-1.0 Lsize= 708kB time=00:00:09.52 bitrate= 609.3kbits/s video:705kB audio:0kB subtitle:0 global headers:0kB muxing overhead 0.505636% [libx264 @ 0000000004d11540] frame I:2 Avg QP:15.07 size: 18186 [libx264 @ 0000000004d11540] frame P:73 Avg QP:16.51 size: 3719 [libx264 @ 0000000004d11540] frame B:165 Avg QP:18.38 size: 2502 [libx264 @ 0000000004d11540] consecutive B-frames: 2.5% 3.3% 42.5% 51.7% [libx264 @ 0000000004d11540] mb I I16..4: 46.2% 33.3% 20.4% [libx264 @ 0000000004d11540] mb P I16..4: 6.8% 2.0% 0.6% P16..4: 29.4% 10.5% 4.6% 0.0% 0.0% skip:46.1% [libx264 @ 0000000004d11540] mb B I16..4: 1.8% 0.7% 0.2% B16..8: 40.9% 6.5% 0.3% direct: 1.2% skip:48.5% L0:52.0% L1:47.5% BI: 0.5% [libx264 @ 0000000004d11540] 8x8 transform intra:24.7% inter:81.3% [libx264 @ 0000000004d11540] direct mvs spatial:93.3% temporal:6.7% [libx264 @ 0000000004d11540] coded y,uvDC,uvAC intra: 10.7% 31.4% 24.9% inter: 2.3% 9.0% 2.9% [libx264 @ 0000000004d11540] i16 v,h,dc,p: 83% 11% 6% 1% [libx264 @ 0000000004d11540] i8 v,h,dc,ddl,ddr,vr,hd,vl,hu: 9% 9% 52% 6% 4% 4% 5% 5% 5% [libx264 @ 0000000004d11540] i4 v,h,dc,ddl,ddr,vr,hd,vl,hu: 22% 11% 44% 5% 4% 3% 3% 4% 3% [libx264 @ 0000000004d11540] i8c dc,h,v,p: 69% 15% 15% 2% [libx264 @ 0000000004d11540] Weighted P-Frames: Y:0.0% UV:0.0% [libx264 @ 0000000004d11540] ref P L0: 48.9% 0.1% 16.8% 17.0% 11.3% 5.8% [libx264 @ 0000000004d11540] ref B L0: 57.7% 21.9% 13.9% 6.4% [libx264 @ 0000000004d11540] ref B L1: 82.4% 17.6% [libx264 @ 0000000004d11540] kb/s:600.61 For me it looks like it converts the video first and afterwards applies the gamma correction on 8-bit clipped video. Does someone have an idea?

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• Troubleshooting unwanted NTP Traffic

  - by Jaxaeon

  A domain controller running Windows Server 2012 is sending NTP and NETBIOS traffic to an address that has never been configured as a time provider. The server logs give no indication that any NTP traffic is failing. The only place I see any evidence of this traffic is in pfSense system logs: (Blocked) Jun 9 08:48:50 DOMAIN 10.0.1.100:123 192.128.127.254:123 UDP (Blocked) Jun 9 08:48:53 DOMAIN 10.0.1.100:137 192.128.127.254:137 UDP As far as I can tell the NTP service is working normally otherwise: DC2.domain.com[10.0.1.101:123]: ICMP: 0ms delay NTP: -0.0131705s offset from DC1.domain.com RefID: DC1.domain.com [10.0.1.100] Stratum: 3 DC1.domain.com *** PDC ***[10.0.1.100:123]: ICMP: 0ms delay NTP: +0.0000000s offset from DC1.domain.com RefID: clock1.albyny.inoc.net [64.246.132.14] Stratum: 2 The time provider NtpClient is currently receiving valid time data from 1.pool.ntp.org,0×1 (ntp.m|0x0|0.0.0.0:123->204.2.134.163:123). The time provider NtpClient is currently receiving valid time data from 0.pool.ntp.org,0×1 (ntp.m|0x0|0.0.0.0:123->64.246.132.14:123). The time service is now synchronizing the system time with the time source 0.pool.ntp.org,0×1 (ntp.m|0x0|0.0.0.0:123->64.246.132.14:123). I've been inside and out of the NTP configuration and cannot find any reason for this traffic. Reverse DNS points the destination address to nothing.attdns.com. pinging nothing.attdns.com from the domain controller in question leads to a response from loopback (127.0.0.2) which makes my head hurt. Any ideas? EDIT1: It should probably be noted that after a dns flush, nslookup 192.128.127.254 returns nothing.attdns.com. 192.128.127.254 is not present in domain.com DNS records. The attdns.com domain is not present in cached lookups. 127.in-addr.arpa is clean of any funkyness. EDIT2: The loopback ping response from nothing.attdns.com is possibly unrelated. Machines on other networks are also displaying this behavior. EDIT3: As mentioned in the comments, I tracked the problem network adapter back to my pfSense VM hosted in esxi 5.5 (I know shame on me for virtualizing a firewall). pfSense was configured to use DC1.domain.com as its primary time provider, but upon changing it back to pool.ntp.org the problem persists. pfSense logs give no indication of NTP misconfiguration. Everywhere I can think to look this VM is identified as 10.0.1.253, so I still have no idea why it’s sending NTP requests as 192.128… Since this firewall was a temporary solution to a problem that no longer exists so I am going to decommission it. EDIT4: The queries were coming from another machine sharing the same virtual adapter as the firewall. The machine has two local adapters: one for LAN, and the other for attached hardware that uses an Ethernet connection. That hardware sits in the the mystery subnet, and the machine is broadcasting NTP requests over both adapters.

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• September 2011 Release of the Ajax Control Toolkit

  - by Stephen Walther

  I’m happy to announce the release of the September 2011 Ajax Control Toolkit. This release has several important new features including: Date ranges – When using the Calendar extender, you can specify a start and end date and a user can pick only those dates which fall within the specified range. This was the fourth top-voted feature request for the Ajax Control Toolkit at CodePlex. Twitter Control – You can use the new Twitter control to display recent tweets associated with a particular Twitter user or tweets which match a search query. Gravatar Control – You can use the new Gravatar control to display a unique image for each user of your website. Users can upload custom images to the Gravatar.com website or the Gravatar control can display a unique, auto-generated, image for a user. You can download this release this very minute by visiting CodePlex: http://AjaxControlToolkit.CodePlex.com Alternatively, you can execute the following command from the Visual Studio NuGet console: Improvements to the Ajax Control Toolkit Calendar Control The Ajax Control Toolkit Calendar extender control is one of the most heavily used controls from the Ajax Control Toolkit. The developers on the Superexpert team spent the last sprint focusing on improving this control. There are three important changes that we made to the Calendar control: we added support for date ranges, we added support for highlighting today’s date, and we made fixes to several bugs related to time zones and daylight savings. Using Calendar Date Ranges One of the top-voted feature requests for the Ajax Control Toolkit was a request to add support for date ranges to the Calendar control (this was the fourth most voted feature request at CodePlex). With the latest release of the Ajax Control Toolkit, the Calendar extender now supports date ranges. For example, the following page illustrates how you can create a popup calendar which allows a user only to pick dates between March 2, 2009 and May 16, 2009. <%@ Page Language="C#" AutoEventWireup="true" CodeBehind="CalendarDateRange.aspx.cs" Inherits="WebApplication1.CalendarDateRange" %> <%@ Register TagPrefix="asp" Namespace="AjaxControlToolkit" Assembly="AjaxControlToolkit" %> <html> <head runat="server"> <title>Calendar Date Range</title> </head> <body> <form id="form1" runat="server"> <asp:ToolkitScriptManager ID="tsm" runat="server" /> <asp:TextBox ID="txtHotelReservationDate" runat="server" /> <asp:CalendarExtender ID="Calendar1" TargetControlID="txtHotelReservationDate" StartDate="3/2/2009" EndDate="5/16/2009" SelectedDate="3/2/2009" runat="server" /> </form> </body> </html> This page contains three controls: an Ajax Control Toolkit ToolkitScriptManager control, a standard ASP.NET TextBox control, and an Ajax Control Toolkit CalendarExtender control. Notice that the Calendar control includes StartDate and EndDate properties which restrict the range of valid dates. The Calendar control shows days, months, and years outside of the valid range as struck out. You cannot select days, months, or years which fall outside of the range. The following video illustrates interacting with the new date range feature: If you want to experiment with a live version of the Ajax Control Toolkit Calendar extender control then you can visit the Calendar Sample Page at the Ajax Control Toolkit Sample Site. Highlighted Today’s Date Another highly requested feature for the Calendar control was support for highlighting today’s date. The Calendar control now highlights the user’s current date regardless of the user’s time zone. Fixes to Time Zone and Daylight Savings Time Bugs We fixed several significant Calendar extender bugs related to time zones and daylight savings time. For example, previously, when you set the Calendar control’s SelectedDate property to the value 1/1/2007 then the selected data would appear as 12/31/2006 or 1/1/2007 or 1/2/2007 depending on the server time zone. For example, if your server time zone was set to Samoa (UTC-11:00), then setting SelectedDate=”1/1/2007” would result in “12/31/2006” being selected in the Calendar. Users of the Calendar extender control found this behavior confusing. After careful consideration, we decided to change the Calendar extender so that it interprets all dates as UTC dates. In other words, if you set StartDate=”1/1/2007” then the Calendar extender parses the date as 1/1/2007 UTC instead of parsing the date according to the server time zone. By interpreting all dates as UTC dates, we avoid all of the reported issues with the SelectedDate property showing the wrong date. Furthermore, when you set the StartDate and EndDate properties, you know that the same StartDate and EndDate will be selected regardless of the time zone associated with the server or associated with the browser. The date 1/1/2007 will always be the date 1/1/2007. The New Twitter Control This release of the Ajax Control Toolkit introduces a new twitter control. You can use the Twitter control to display recent tweets associated with a particular twitter user. You also can use this control to show the results of a twitter search. The following page illustrates how you can use the Twitter control to display recent tweets made by Scott Hanselman: <%@ Page Language="C#" AutoEventWireup="true" CodeBehind="TwitterProfile.aspx.cs" Inherits="WebApplication1.TwitterProfile" %> <%@ Register TagPrefix="asp" Namespace="AjaxControlToolkit" Assembly="AjaxControlToolkit" %> <html > <head runat="server"> <title>Twitter Profile</title> </head> <body> <form id="form1" runat="server"> <asp:ToolkitScriptManager ID="tsm" runat="server" /> <asp:Twitter ID="Twitter1" ScreenName="shanselman" runat="server" /> </form> </body> </html> This page includes two Ajax Control Toolkit controls: the ToolkitScriptManager control and the Twitter control. The Twitter control is set to display tweets from Scott Hanselman (shanselman): You also can use the Twitter control to display the results of a search query. For example, the following page displays all recent tweets related to the Ajax Control Toolkit: Twitter limits the number of times that you can interact with their API in an hour. Twitter recommends that you cache results on the server (https://dev.twitter.com/docs/rate-limiting). By default, the Twitter control caches results on the server for a duration of 5 minutes. You can modify the cache duration by assigning a value (in seconds) to the Twitter control's CacheDuration property. The Twitter control wraps a standard ASP.NET ListView control. You can customize the appearance of the Twitter control by modifying its LayoutTemplate, StatusTemplate, AlternatingStatusTemplate, and EmptyDataTemplate. To learn more about the new Twitter control, visit the live Twitter Sample Page. The New Gravatar Control The September 2011 release of the Ajax Control Toolkit also includes a new Gravatar control. This control makes it easy to display a unique image for each user of your website. A Gravatar is associated with an email address. You can visit Gravatar.com and upload an image and associate the image with your email address. That way, every website which uses Gravatars (such as the www.ASP.NET website) will display your image next to your name. For example, I visited the Gravatar.com website and associated an image of a Koala Bear with the email address [email protected]. The following page illustrates how you can use the Gravatar control to display the Gravatar image associated with the [email protected] email address: <%@ Page Language="C#" AutoEventWireup="true" CodeBehind="GravatarDemo.aspx.cs" Inherits="WebApplication1.GravatarDemo" %> <%@ Register TagPrefix="asp" Namespace="AjaxControlToolkit" Assembly="AjaxControlToolkit" %> <html xmlns="http://www.w3.org/1999/xhtml"> <head id="Head1" runat="server"> <title>Gravatar Demo</title> </head> <body> <form id="form1" runat="server"> <asp:ToolkitScriptManager ID="tsm" runat="server" /> <asp:Gravatar ID="Gravatar1" Email="[email protected]" runat="server" /> </form> </body> </html> The page above simply displays the Gravatar image associated with the [email protected] email address: If a user has not uploaded an image to Gravatar.com then you can auto-generate a unique image for the user from the user email address. The Gravatar control supports four types of auto-generated images: Identicon -- A different geometric pattern is generated for each unrecognized email. MonsterId -- A different image of a monster is generated for each unrecognized email. Wavatar -- A different image of a face is generated for each unrecognized email. Retro -- A different 8-bit arcade-style face is generated for each unrecognized email. For example, there is no Gravatar image associated with the email address [email protected]. The following page displays an auto-generated MonsterId for this email address: <%@ Page Language="C#" AutoEventWireup="true" CodeBehind="GravatarMonster.aspx.cs" Inherits="WebApplication1.GravatarMonster" %> <%@ Register TagPrefix="asp" Namespace="AjaxControlToolkit" Assembly="AjaxControlToolkit" %> <html xmlns="http://www.w3.org/1999/xhtml"> <head id="Head1" runat="server"> <title>Gravatar Monster</title> </head> <body> <form id="form1" runat="server"> <asp:ToolkitScriptManager ID="tsm" runat="server" /> <asp:Gravatar ID="Gravatar1" Email="[email protected]" DefaultImageBehavior="MonsterId" runat="server" /> </form> </body> </html> The page above generates the following image automatically from the supplied email address: To learn more about the properties of the new Gravatar control, visit the live Gravatar Sample Page. ASP.NET Connections Talk on the Ajax Control Toolkit If you are interested in learning more about the changes that we are making to the Ajax Control Toolkit then please come to my talk on the Ajax Control Toolkit at the upcoming ASP.NET Connections conference. In the talk, I will present a summary of the changes that we have made to the Ajax Control Toolkit over the last several months and discuss our future plans. Do you have ideas for new Ajax Control Toolkit controls? Ideas for improving the toolkit? Come to my talk – I would love to hear from you. You can register for the ASP.NET Connections conference by visiting the following website: Register for ASP.NET Connections   Summary The previous release of the Ajax Control Toolkit – the July 2011 Release – has had over 100,000 downloads. That is a huge number of developers who are working with the Ajax Control Toolkit. We are really excited about the new features which we added to the Ajax Control Toolkit in the latest September sprint. We hope that you find the updated Calender control, the new Twitter control, and the new Gravatar control valuable when building your ASP.NET Web Forms applications.

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• Moving from Winforms to WPF

  - by Elmex

  I am a long time experienced Windows Forms developer, but now it's time to move to WPF because a new WPF project is comming soon to me and I have only a short lead time to prepare myself to learn WPF. What is the best way for a experienced Winforms devleoper? Can you give me some hints and recommendations to learn WPF in a very short time! Are there simple sample WPF solutions and short (video) tutorials? Which books do you recommend? Is www.windowsclient.net a good starting point? Are there alternatives to the official Microsoft site? Thanks in advance for your help!

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• Improving Partitioned Table Join Performance

  - by Paul White

  The query optimizer does not always choose an optimal strategy when joining partitioned tables. This post looks at an example, showing how a manual rewrite of the query can almost double performance, while reducing the memory grant to almost nothing. Test Data The two tables in this example use a common partitioning partition scheme. The partition function uses 41 equal-size partitions: CREATE PARTITION FUNCTION PFT (integer) AS RANGE RIGHT FOR VALUES ( 125000, 250000, 375000, 500000, 625000, 750000, 875000, 1000000, 1125000, 1250000, 1375000, 1500000, 1625000, 1750000, 1875000, 2000000, 2125000, 2250000, 2375000, 2500000, 2625000, 2750000, 2875000, 3000000, 3125000, 3250000, 3375000, 3500000, 3625000, 3750000, 3875000, 4000000, 4125000, 4250000, 4375000, 4500000, 4625000, 4750000, 4875000, 5000000 ); GO CREATE PARTITION SCHEME PST AS PARTITION PFT ALL TO ([PRIMARY]); There two tables are: CREATE TABLE dbo.T1 ( TID integer NOT NULL IDENTITY(0,1), Column1 integer NOT NULL, Padding binary(100) NOT NULL DEFAULT 0x,   CONSTRAINT PK_T1 PRIMARY KEY CLUSTERED (TID) ON PST (TID) );   CREATE TABLE dbo.T2 ( TID integer NOT NULL, Column1 integer NOT NULL, Padding binary(100) NOT NULL DEFAULT 0x,   CONSTRAINT PK_T2 PRIMARY KEY CLUSTERED (TID, Column1) ON PST (TID) ); The next script loads 5 million rows into T1 with a pseudo-random value between 1 and 5 for Column1. The table is partitioned on the IDENTITY column TID: INSERT dbo.T1 WITH (TABLOCKX) (Column1) SELECT (ABS(CHECKSUM(NEWID())) % 5) + 1 FROM dbo.Numbers AS N WHERE n BETWEEN 1 AND 5000000; In case you don’t already have an auxiliary table of numbers lying around, here’s a script to create one with 10 million rows: CREATE TABLE dbo.Numbers (n bigint PRIMARY KEY);   WITH L0 AS(SELECT 1 AS c UNION ALL SELECT 1), L1 AS(SELECT 1 AS c FROM L0 AS A CROSS JOIN L0 AS B), L2 AS(SELECT 1 AS c FROM L1 AS A CROSS JOIN L1 AS B), L3 AS(SELECT 1 AS c FROM L2 AS A CROSS JOIN L2 AS B), L4 AS(SELECT 1 AS c FROM L3 AS A CROSS JOIN L3 AS B), L5 AS(SELECT 1 AS c FROM L4 AS A CROSS JOIN L4 AS B), Nums AS(SELECT ROW_NUMBER() OVER (ORDER BY (SELECT NULL)) AS n FROM L5) INSERT dbo.Numbers WITH (TABLOCKX) SELECT TOP (10000000) n FROM Nums ORDER BY n OPTION (MAXDOP 1); Table T1 contains data like this: Next we load data into table T2. The relationship between the two tables is that table 2 contains ‘n’ rows for each row in table 1, where ‘n’ is determined by the value in Column1 of table T1. There is nothing particularly special about the data or distribution, by the way. INSERT dbo.T2 WITH (TABLOCKX) (TID, Column1) SELECT T.TID, N.n FROM dbo.T1 AS T JOIN dbo.Numbers AS N ON N.n >= 1 AND N.n <= T.Column1; Table T2 ends up containing about 15 million rows: The primary key for table T2 is a combination of TID and Column1. The data is partitioned according to the value in column TID alone. Partition Distribution The following query shows the number of rows in each partition of table T1: SELECT PartitionID = CA1.P, NumRows = COUNT_BIG(*) FROM dbo.T1 AS T CROSS APPLY (VALUES ($PARTITION.PFT(TID))) AS CA1 (P) GROUP BY CA1.P ORDER BY CA1.P; There are 40 partitions containing 125,000 rows (40 * 125k = 5m rows). The rightmost partition remains empty. The next query shows the distribution for table 2: SELECT PartitionID = CA1.P, NumRows = COUNT_BIG(*) FROM dbo.T2 AS T CROSS APPLY (VALUES ($PARTITION.PFT(TID))) AS CA1 (P) GROUP BY CA1.P ORDER BY CA1.P; There are roughly 375,000 rows in each partition (the rightmost partition is also empty): Ok, that’s the test data done. Test Query and Execution Plan The task is to count the rows resulting from joining tables 1 and 2 on the TID column: SET STATISTICS IO ON; DECLARE @s datetime2 = SYSUTCDATETIME();   SELECT COUNT_BIG(*) FROM dbo.T1 AS T1 JOIN dbo.T2 AS T2 ON T2.TID = T1.TID;   SELECT DATEDIFF(Millisecond, @s, SYSUTCDATETIME()); SET STATISTICS IO OFF; The optimizer chooses a plan using parallel hash join, and partial aggregation: The Plan Explorer plan tree view shows accurate cardinality estimates and an even distribution of rows across threads (click to enlarge the image): With a warm data cache, the STATISTICS IO output shows that no physical I/O was needed, and all 41 partitions were touched: Running the query without actual execution plan or STATISTICS IO information for maximum performance, the query returns in around 2600ms. Execution Plan Analysis The first step toward improving on the execution plan produced by the query optimizer is to understand how it works, at least in outline. The two parallel Clustered Index Scans use multiple threads to read rows from tables T1 and T2. Parallel scan uses a demand-based scheme where threads are given page(s) to scan from the table as needed. This arrangement has certain important advantages, but does result in an unpredictable distribution of rows amongst threads. The point is that multiple threads cooperate to scan the whole table, but it is impossible to predict which rows end up on which threads. For correct results from the parallel hash join, the execution plan has to ensure that rows from T1 and T2 that might join are processed on the same thread. For example, if a row from T1 with join key value ‘1234’ is placed in thread 5’s hash table, the execution plan must guarantee that any rows from T2 that also have join key value ‘1234’ probe thread 5’s hash table for matches. The way this guarantee is enforced in this parallel hash join plan is by repartitioning rows to threads after each parallel scan. The two repartitioning exchanges route rows to threads using a hash function over the hash join keys. The two repartitioning exchanges use the same hash function so rows from T1 and T2 with the same join key must end up on the same hash join thread. Expensive Exchanges This business of repartitioning rows between threads can be very expensive, especially if a large number of rows is involved. The execution plan selected by the optimizer moves 5 million rows through one repartitioning exchange and around 15 million across the other. As a first step toward removing these exchanges, consider the execution plan selected by the optimizer if we join just one partition from each table, disallowing parallelism: SELECT COUNT_BIG(*) FROM dbo.T1 AS T1 JOIN dbo.T2 AS T2 ON T2.TID = T1.TID WHERE $PARTITION.PFT(T1.TID) = 1 AND $PARTITION.PFT(T2.TID) = 1 OPTION (MAXDOP 1); The optimizer has chosen a (one-to-many) merge join instead of a hash join. The single-partition query completes in around 100ms. If everything scaled linearly, we would expect that extending this strategy to all 40 populated partitions would result in an execution time around 4000ms. Using parallelism could reduce that further, perhaps to be competitive with the parallel hash join chosen by the optimizer. This raises a question. If the most efficient way to join one partition from each of the tables is to use a merge join, why does the optimizer not choose a merge join for the full query? Forcing a Merge Join Let’s force the optimizer to use a merge join on the test query using a hint: SELECT COUNT_BIG(*) FROM dbo.T1 AS T1 JOIN dbo.T2 AS T2 ON T2.TID = T1.TID OPTION (MERGE JOIN); This is the execution plan selected by the optimizer: This plan results in the same number of logical reads reported previously, but instead of 2600ms the query takes 5000ms. The natural explanation for this drop in performance is that the merge join plan is only using a single thread, whereas the parallel hash join plan could use multiple threads. Parallel Merge Join We can get a parallel merge join plan using the same query hint as before, and adding trace flag 8649: SELECT COUNT_BIG(*) FROM dbo.T1 AS T1 JOIN dbo.T2 AS T2 ON T2.TID = T1.TID OPTION (MERGE JOIN, QUERYTRACEON 8649); The execution plan is: This looks promising. It uses a similar strategy to distribute work across threads as seen for the parallel hash join. In practice though, performance is disappointing. On a typical run, the parallel merge plan runs for around 8400ms; slower than the single-threaded merge join plan (5000ms) and much worse than the 2600ms for the parallel hash join. We seem to be going backwards! The logical reads for the parallel merge are still exactly the same as before, with no physical IOs. The cardinality estimates and thread distribution are also still very good (click to enlarge): A big clue to the reason for the poor performance is shown in the wait statistics (captured by Plan Explorer Pro): CXPACKET waits require careful interpretation, and are most often benign, but in this case excessive waiting occurs at the repartitioning exchanges. Unlike the parallel hash join, the repartitioning exchanges in this plan are order-preserving ‘merging’ exchanges (because merge join requires ordered inputs): Parallelism works best when threads can just grab any available unit of work and get on with processing it. Preserving order introduces inter-thread dependencies that can easily lead to significant waits occurring. In extreme cases, these dependencies can result in an intra-query deadlock, though the details of that will have to wait for another time to explore in detail. The potential for waits and deadlocks leads the query optimizer to cost parallel merge join relatively highly, especially as the degree of parallelism (DOP) increases. This high costing resulted in the optimizer choosing a serial merge join rather than parallel in this case. The test results certainly confirm its reasoning. Collocated Joins In SQL Server 2008 and later, the optimizer has another available strategy when joining tables that share a common partition scheme. This strategy is a collocated join, also known as as a per-partition join. It can be applied in both serial and parallel execution plans, though it is limited to 2-way joins in the current optimizer. Whether the optimizer chooses a collocated join or not depends on cost estimation. The primary benefits of a collocated join are that it eliminates an exchange and requires less memory, as we will see next. Costing and Plan Selection The query optimizer did consider a collocated join for our original query, but it was rejected on cost grounds. The parallel hash join with repartitioning exchanges appeared to be a cheaper option. There is no query hint to force a collocated join, so we have to mess with the costing framework to produce one for our test query. Pretending that IOs cost 50 times more than usual is enough to convince the optimizer to use collocated join with our test query: -- Pretend IOs are 50x cost temporarily DBCC SETIOWEIGHT(50);   -- Co-located hash join SELECT COUNT_BIG(*) FROM dbo.T1 AS T1 JOIN dbo.T2 AS T2 ON T2.TID = T1.TID OPTION (RECOMPILE);   -- Reset IO costing DBCC SETIOWEIGHT(1); Collocated Join Plan The estimated execution plan for the collocated join is: The Constant Scan contains one row for each partition of the shared partitioning scheme, from 1 to 41. The hash repartitioning exchanges seen previously are replaced by a single Distribute Streams exchange using Demand partitioning. Demand partitioning means that the next partition id is given to the next parallel thread that asks for one. My test machine has eight logical processors, and all are available for SQL Server to use. As a result, there are eight threads in the single parallel branch in this plan, each processing one partition from each table at a time. Once a thread finishes processing a partition, it grabs a new partition number from the Distribute Streams exchange…and so on until all partitions have been processed. It is important to understand that the parallel scans in this plan are different from the parallel hash join plan. Although the scans have the same parallelism icon, tables T1 and T2 are not being co-operatively scanned by multiple threads in the same way. Each thread reads a single partition of T1 and performs a hash match join with the same partition from table T2. The properties of the two Clustered Index Scans show a Seek Predicate (unusual for a scan!) limiting the rows to a single partition: The crucial point is that the join between T1 and T2 is on TID, and TID is the partitioning column for both tables. A thread that processes partition ‘n’ is guaranteed to see all rows that can possibly join on TID for that partition. In addition, no other thread will see rows from that partition, so this removes the need for repartitioning exchanges. CPU and Memory Efficiency Improvements The collocated join has removed two expensive repartitioning exchanges and added a single exchange processing 41 rows (one for each partition id). Remember, the parallel hash join plan exchanges had to process 5 million and 15 million rows. The amount of processor time spent on exchanges will be much lower in the collocated join plan. In addition, the collocated join plan has a maximum of 8 threads processing single partitions at any one time. The 41 partitions will all be processed eventually, but a new partition is not started until a thread asks for it. Threads can reuse hash table memory for the new partition. The parallel hash join plan also had 8 hash tables, but with all 5,000,000 build rows loaded at the same time. The collocated plan needs memory for only 8 * 125,000 = 1,000,000 rows at any one time. Collocated Hash Join Performance The collated join plan has disappointing performance in this case. The query runs for around 25,300ms despite the same IO statistics as usual. This is much the worst result so far, so what went wrong? It turns out that cardinality estimation for the single partition scans of table T1 is slightly low. The properties of the Clustered Index Scan of T1 (graphic immediately above) show the estimation was for 121,951 rows. This is a small shortfall compared with the 125,000 rows actually encountered, but it was enough to cause the hash join to spill to physical tempdb: A level 1 spill doesn’t sound too bad, until you realize that the spill to tempdb probably occurs for each of the 41 partitions. As a side note, the cardinality estimation error is a little surprising because the system tables accurately show there are 125,000 rows in every partition of T1. Unfortunately, the optimizer uses regular column and index statistics to derive cardinality estimates here rather than system table information (e.g. sys.partitions). Collocated Merge Join We will never know how well the collocated parallel hash join plan might have worked without the cardinality estimation error (and the resulting 41 spills to tempdb) but we do know: Merge join does not require a memory grant; and Merge join was the optimizer’s preferred join option for a single partition join Putting this all together, what we would really like to see is the same collocated join strategy, but using merge join instead of hash join. Unfortunately, the current query optimizer cannot produce a collocated merge join; it only knows how to do collocated hash join. So where does this leave us? CROSS APPLY sys.partitions We can try to write our own collocated join query. We can use sys.partitions to find the partition numbers, and CROSS APPLY to get a count per partition, with a final step to sum the partial counts. The following query implements this idea: SELECT row_count = SUM(Subtotals.cnt) FROM ( -- Partition numbers SELECT p.partition_number FROM sys.partitions AS p WHERE p.[object_id] = OBJECT_ID(N'T1', N'U') AND p.index_id = 1 ) AS P CROSS APPLY ( -- Count per collocated join SELECT cnt = COUNT_BIG(*) FROM dbo.T1 AS T1 JOIN dbo.T2 AS T2 ON T2.TID = T1.TID WHERE $PARTITION.PFT(T1.TID) = p.partition_number AND $PARTITION.PFT(T2.TID) = p.partition_number ) AS SubTotals; The estimated plan is: The cardinality estimates aren’t all that good here, especially the estimate for the scan of the system table underlying the sys.partitions view. Nevertheless, the plan shape is heading toward where we would like to be. Each partition number from the system table results in a per-partition scan of T1 and T2, a one-to-many Merge Join, and a Stream Aggregate to compute the partial counts. The final Stream Aggregate just sums the partial counts. Execution time for this query is around 3,500ms, with the same IO statistics as always. This compares favourably with 5,000ms for the serial plan produced by the optimizer with the OPTION (MERGE JOIN) hint. This is another case of the sum of the parts being less than the whole – summing 41 partial counts from 41 single-partition merge joins is faster than a single merge join and count over all partitions. Even so, this single-threaded collocated merge join is not as quick as the original parallel hash join plan, which executed in 2,600ms. On the positive side, our collocated merge join uses only one logical processor and requires no memory grant. The parallel hash join plan used 16 threads and reserved 569 MB of memory:   Using a Temporary Table Our collocated merge join plan should benefit from parallelism. The reason parallelism is not being used is that the query references a system table. We can work around that by writing the partition numbers to a temporary table (or table variable): SET STATISTICS IO ON; DECLARE @s datetime2 = SYSUTCDATETIME();   CREATE TABLE #P ( partition_number integer PRIMARY KEY);   INSERT #P (partition_number) SELECT p.partition_number FROM sys.partitions AS p WHERE p.[object_id] = OBJECT_ID(N'T1', N'U') AND p.index_id = 1;   SELECT row_count = SUM(Subtotals.cnt) FROM #P AS p CROSS APPLY ( SELECT cnt = COUNT_BIG(*) FROM dbo.T1 AS T1 JOIN dbo.T2 AS T2 ON T2.TID = T1.TID WHERE $PARTITION.PFT(T1.TID) = p.partition_number AND $PARTITION.PFT(T2.TID) = p.partition_number ) AS SubTotals;   DROP TABLE #P;   SELECT DATEDIFF(Millisecond, @s, SYSUTCDATETIME()); SET STATISTICS IO OFF; Using the temporary table adds a few logical reads, but the overall execution time is still around 3500ms, indistinguishable from the same query without the temporary table. The problem is that the query optimizer still doesn’t choose a parallel plan for this query, though the removal of the system table reference means that it could if it chose to: In fact the optimizer did enter the parallel plan phase of query optimization (running search 1 for a second time): Unfortunately, the parallel plan found seemed to be more expensive than the serial plan. This is a crazy result, caused by the optimizer’s cost model not reducing operator CPU costs on the inner side of a nested loops join. Don’t get me started on that, we’ll be here all night. In this plan, everything expensive happens on the inner side of a nested loops join. Without a CPU cost reduction to compensate for the added cost of exchange operators, candidate parallel plans always look more expensive to the optimizer than the equivalent serial plan. Parallel Collocated Merge Join We can produce the desired parallel plan using trace flag 8649 again: SELECT row_count = SUM(Subtotals.cnt) FROM #P AS p CROSS APPLY ( SELECT cnt = COUNT_BIG(*) FROM dbo.T1 AS T1 JOIN dbo.T2 AS T2 ON T2.TID = T1.TID WHERE $PARTITION.PFT(T1.TID) = p.partition_number AND $PARTITION.PFT(T2.TID) = p.partition_number ) AS SubTotals OPTION (QUERYTRACEON 8649); The actual execution plan is: One difference between this plan and the collocated hash join plan is that a Repartition Streams exchange operator is used instead of Distribute Streams. The effect is similar, though not quite identical. The Repartition uses round-robin partitioning, meaning the next partition id is pushed to the next thread in sequence. The Distribute Streams exchange seen earlier used Demand partitioning, meaning the next partition id is pulled across the exchange by the next thread that is ready for more work. There are subtle performance implications for each partitioning option, but going into that would again take us too far off the main point of this post. Performance The important thing is the performance of this parallel collocated merge join – just 1350ms on a typical run. The list below shows all the alternatives from this post (all timings include creation, population, and deletion of the temporary table where appropriate) from quickest to slowest: Collocated parallel merge join: 1350ms Parallel hash join: 2600ms Collocated serial merge join: 3500ms Serial merge join: 5000ms Parallel merge join: 8400ms Collated parallel hash join: 25,300ms (hash spill per partition) The parallel collocated merge join requires no memory grant (aside from a paltry 1.2MB used for exchange buffers). This plan uses 16 threads at DOP 8; but 8 of those are (rather pointlessly) allocated to the parallel scan of the temporary table. These are minor concerns, but it turns out there is a way to address them if it bothers you. Parallel Collocated Merge Join with Demand Partitioning This final tweak replaces the temporary table with a hard-coded list of partition ids (dynamic SQL could be used to generate this query from sys.partitions): SELECT row_count = SUM(Subtotals.cnt) FROM ( VALUES (1),(2),(3),(4),(5),(6),(7),(8),(9),(10), (11),(12),(13),(14),(15),(16),(17),(18),(19),(20), (21),(22),(23),(24),(25),(26),(27),(28),(29),(30), (31),(32),(33),(34),(35),(36),(37),(38),(39),(40),(41) ) AS P (partition_number) CROSS APPLY ( SELECT cnt = COUNT_BIG(*) FROM dbo.T1 AS T1 JOIN dbo.T2 AS T2 ON T2.TID = T1.TID WHERE $PARTITION.PFT(T1.TID) = p.partition_number AND $PARTITION.PFT(T2.TID) = p.partition_number ) AS SubTotals OPTION (QUERYTRACEON 8649); The actual execution plan is: The parallel collocated hash join plan is reproduced below for comparison: The manual rewrite has another advantage that has not been mentioned so far: the partial counts (per partition) can be computed earlier than the partial counts (per thread) in the optimizer’s collocated join plan. The earlier aggregation is performed by the extra Stream Aggregate under the nested loops join. The performance of the parallel collocated merge join is unchanged at around 1350ms. Final Words It is a shame that the current query optimizer does not consider a collocated merge join (Connect item closed as Won’t Fix). The example used in this post showed an improvement in execution time from 2600ms to 1350ms using a modestly-sized data set and limited parallelism. In addition, the memory requirement for the query was almost completely eliminated  – down from 569MB to 1.2MB. The problem with the parallel hash join selected by the optimizer is that it attempts to process the full data set all at once (albeit using eight threads). It requires a large memory grant to hold all 5 million rows from table T1 across the eight hash tables, and does not take advantage of the divide-and-conquer opportunity offered by the common partitioning. The great thing about the collocated join strategies is that each parallel thread works on a single partition from both tables, reading rows, performing the join, and computing a per-partition subtotal, before moving on to a new partition. From a thread’s point of view… If you have trouble visualizing what is happening from just looking at the parallel collocated merge join execution plan, let’s look at it again, but from the point of view of just one thread operating between the two Parallelism (exchange) operators. Our thread picks up a single partition id from the Distribute Streams exchange, and starts a merge join using ordered rows from partition 1 of table T1 and partition 1 of table T2. By definition, this is all happening on a single thread. As rows join, they are added to a (per-partition) count in the Stream Aggregate immediately above the Merge Join. Eventually, either T1 (partition 1) or T2 (partition 1) runs out of rows and the merge join stops. The per-partition count from the aggregate passes on through the Nested Loops join to another Stream Aggregate, which is maintaining a per-thread subtotal. Our same thread now picks up a new partition id from the exchange (say it gets id 9 this time). The count in the per-partition aggregate is reset to zero, and the processing of partition 9 of both tables proceeds just as it did for partition 1, and on the same thread. Each thread picks up a single partition id and processes all the data for that partition, completely independently from other threads working on other partitions. One thread might eventually process partitions (1, 9, 17, 25, 33, 41) while another is concurrently processing partitions (2, 10, 18, 26, 34) and so on for the other six threads at DOP 8. The point is that all 8 threads can execute independently and concurrently, continuing to process new partitions until the wider job (of which the thread has no knowledge!) is done. This divide-and-conquer technique can be much more efficient than simply splitting the entire workload across eight threads all at once. Related Reading Understanding and Using Parallelism in SQL Server Parallel Execution Plans Suck © 2013 Paul White – All Rights Reserved Twitter: @SQL_Kiwi

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• Back from Teched US

  - by gsusx

  It's been a few weeks since I last blogged and, trust me, I am not happy about it :( I have been crazily busy with some of our projects at Tellago which you are going to hear more about in the upcoming weeks :) I was so busy that I didn't even have time to blog about my sessions at Teched US last week. This year I ended up presenting three sessions on three different tracks: BIE403 | Real-Time Business Intelligence with Microsoft SQL Server 2008 R2 Session Type: Breakout Session Real-time business...(read more)

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• Create a Persistent Bootable Ubuntu USB Flash Drive

  - by Trevor Bekolay

  Don’t feel like reinstalling an antivirus program every time you boot up your Ubuntu flash drive? We’ll show you how to create a bootable Ubuntu flash drive that will remember your settings, installed programs, and more! Previously, we showed you how to create a bootable Ubuntu flash drive that would reset to its initial state every time you booted it up. This is great if you’re worried about messing something up, and want to start fresh every time you start tinkering with Ubuntu. However, if you’re using the Ubuntu flash drive to diagnose and solve problems with your PC, you might find that a lot of problems require guess-and-test cycles. It would be great if the settings you change in Ubuntu and the programs you install stay installed the next time you boot it up. Fortunately, Universal USB Installer, a great little program from Pen Drive Linux, can do just that! Note: You will need a USB drive at least 2 GB large. Make sure you back up any files on the flash drive because this process will format the drive, removing any files currently on it. Once Ubuntu has been installed on the flash drive, you can move those files back if there is enough space. Put Ubuntu on your flash drive Universal-USB-Installer.exe does not need to be installed, so just double click on it to run it wherever you downloaded it. Click Yes if you get a UAC prompt, and you will be greeted with this window. Click I Agree. In the drop-down box on the next screen, select Ubuntu 9.10 Desktop i386. Don’t worry if you normally use 64-bit operating systems – the 32-bit version of Ubuntu 9.10 will still work fine. Some useful tools do not have 64-bit versions, so unless you’re planning on switching to Ubuntu permanently, the 32-bit version will work best. If you don’t have a copy of the Ubuntu 9.10 CD downloaded, then click on the checkbox to Download the ISO. You’ll be prompted to launch a web browser; click Yes. The download should start immediately. When it’s finished, return the the Universal USB Installer and click on Browse to navigate to the ISO file you just downloaded. Click OK and the text field will be populated with the path to the ISO file. Select the drive letter that corresponds to the flash drive that you would like to use from the dropdown box. If you’ve backed up the files on this drive, we recommend checking the box to format the drive. Finally, you have to choose how much space you would like to set aside for the settings and programs that will be stored on the flash drive. Considering that Ubuntu itself only takes up around 700 MB, 1 GB should be plenty, but we’re choosing 2 GB in this example because we have lots of space on this USB drive. Click on the Create button and then make yourself a sandwich – it will take some time to install no matter how fast your PC is. Eventually it will finish. Click Close. Now you have a flash drive that will boot into a fully capable Ubuntu installation, and any changes you make will persist the next time you boot it up! Boot into Ubuntu If you’re not sure how to set your computer to boot using the USB drive, then check out the How to Boot Into Ubuntu section of our previous article on creating bootable USB drives, or refer to your motherboard’s manual. Once your computer is set to boot using the USB drive, you’ll be greeted with splash screen with some options. Press Enter to boot into Ubuntu. The first time you do this, it may take some time to boot up. Fortunately, we’ve found that the process speeds up on subsequent boots. You’ll be greeted with the Ubuntu desktop. Now, if you change settings like the desktop resolution, or install a program, those changes will be permanently stored on the USB drive! We installed avast! Antivirus, and on the next boot, found that it was still in the Accessories menu where we left it. Conclusion We think that a bootable Ubuntu USB flash drive is a great tool to have around in case your PC has problems booting otherwise. By having the changes you make persist, you can customize your Ubuntu installation to be the ultimate computer repair toolkit! Download Universal USB Installer from Pen Drive Linux Similar Articles Productive Geek Tips Create a Bootable Ubuntu USB Flash Drive the Easy WayCreate a Bootable Ubuntu 9.10 USB Flash DriveReset Your Ubuntu Password Easily from the Live CDHow-To Geek on Lifehacker: Control Your Computer with Shortcuts & Speed Up Vista SetupHow To Setup a USB Flash Drive to Install Windows 7 TouchFreeze Alternative in AutoHotkey The Icy Undertow Desktop Windows Home Server – Backup to LAN The Clear & Clean Desktop Use This Bookmarklet to Easily Get Albums Use AutoHotkey to Assign a Hotkey to a Specific Window Latest Software Reviews Tinyhacker Random Tips DVDFab 6 Revo Uninstaller Pro Registry Mechanic 9 for Windows PC Tools Internet Security Suite 2010 Test Drive Windows 7 Online Download Wallpapers From National Geographic Site Spyware Blaster v4.3 Yes, it’s Patch Tuesday Generate Stunning Tag Clouds With Tagxedo Install, Remove and HIDE Fonts in Windows 7

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• Moving from Winforms to WPF

  - by Elmex

  I am a long time experienced Windows Forms developer, but now it's time to move to WPF because a new WPF project is comming soon to me and I have only a short lead time to prepare myself to learn WPF. What is the best way for a experienced Winforms devleoper? Can you give me some hints and recommendations to learn WPF in a very short time! Are there simple sample WPF solutions and short (video) tutorials? Which books do you recommend? Is www.windowsclient.net a good starting point? Are there alternatives to the official Microsoft site? Thanks in advance for your help!

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• External Monitors shut off when Laptop Lid closes

  - by John Lanz

  I have researched the solution... gconftool-2 --type string --set /apps/gnome-power-manager/buttons/lid_ac "nothing" does not fix it. I have two external monitors and when I close my lid the settings are reset and the laptop's monitor is set to the default. Thanks! gsettings list-recursively org.gnome.settings-daemon.plugins.power org.gnome.settings-daemon.plugins.power active true org.gnome.settings-daemon.plugins.power button-hibernate 'nothing' org.gnome.settings-daemon.plugins.power button-power 'nothing' org.gnome.settings-daemon.plugins.power button-sleep 'nothing' org.gnome.settings-daemon.plugins.power button-suspend 'nothing' org.gnome.settings-daemon.plugins.power critical-battery-action 'suspend' org.gnome.settings-daemon.plugins.power idle-brightness 30 org.gnome.settings-daemon.plugins.power idle-dim-ac false org.gnome.settings-daemon.plugins.power idle-dim-battery true org.gnome.settings-daemon.plugins.power idle-dim-time 10 org.gnome.settings-daemon.plugins.power lid-close-ac-action 'nothing' org.gnome.settings-daemon.plugins.power lid-close-battery-action 'nothing' org.gnome.settings-daemon.plugins.power notify-perhaps-recall true org.gnome.settings-daemon.plugins.power percentage-action 2 org.gnome.settings-daemon.plugins.power percentage-critical 3 org.gnome.settings-daemon.plugins.power percentage-low 10 org.gnome.settings-daemon.plugins.power priority 1 org.gnome.settings-daemon.plugins.power sleep-display-ac 600 org.gnome.settings-daemon.plugins.power sleep-display-battery 600 org.gnome.settings-daemon.plugins.power sleep-inactive-ac false org.gnome.settings-daemon.plugins.power sleep-inactive-ac-timeout 0 org.gnome.settings-daemon.plugins.power sleep-inactive-ac-type 'suspend' org.gnome.settings-daemon.plugins.power sleep-inactive-battery true org.gnome.settings-daemon.plugins.power sleep-inactive-battery-timeout 0 org.gnome.settings-daemon.plugins.power sleep-inactive-battery-type 'suspend' org.gnome.settings-daemon.plugins.power time-action 120 org.gnome.settings-daemon.plugins.power time-critical 300 org.gnome.settings-daemon.plugins.power time-low 1200 org.gnome.settings-daemon.plugins.power use-time-for-policy true

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• Error : Member 'D-T-D' in the Period dimension has no value for the Period Type property

  - by RahulS

  Workaround for LCM EPMA deploy errors: Error : Member 'D-T-D' in the Period dimension has no value for the Period  Type property.  Error : Member name 'D-T-D' in the Period dimension is only valid when Period  Type is set to 'DTS Time Period'.  Error : Member 'W-T-D' in the Period dimension has no value for the Period  Type property.  Error : Member name 'W-T-D' in the Period dimension is only valid when Period  Type is set to 'DTS Time Period'.  Error : Member 'M-T-D' in the Period dimension has no value for the Period  Type property.  Error : Member name 'M-T-D' in the Period dimension is only valid when Period  Type is set to 'DTS Time Period'.  Error : Member 'Q-T-D' in the Period dimension has no value for the Period  Type property.  Error : Member name 'Q-T-D' in the Period dimension is only valid when Period  Type is set to 'DTS Time Period'.  Error : Member 'P-T-D' in the Period dimension has no value for the Period  Type property.  Error : Member name 'P-T-D' in the Period dimension is only valid when Period  Type is set to 'DTS Time Period'.  Error : Member 'S-T-D' in the Period dimension has no value for the Period  Type property.  Error : Member name 'S-T-D' in the Period dimension is only valid when Period  Type is set to 'DTS Time Period'.  Error : Member 'Y-T-D' in the Period dimension has no value for the Period  Type property.  Error : Member name 'Y-T-D' in the Period dimension is only valid when Period  Type is set to 'DTS Time Period'.  Error : Member 'H-T-D' in the Period dimension has no value for the Period  Type property.  Error : Member name 'H-T-D' in the Period dimension is only valid when Period  Type is set to 'DTS Time Period'. Fix 1. Edit the Period dimension LCM artifact (Keep the back up of the file before editing.)  2. Delete the DTS members (for example as mentioned below) in the Period dimension hierarchy section.   #root|D-T-D|True||||||||||||||||   #root|W-T-D|True||||||||||||||||   #root|M-T-D|True||||||||||||||||   #root|Q-T-D|True||||||||||||||||   #root|P-T-D|True||||||||||||||||   #root|S-T-D|True||||||||||||||||   #root|Y-T-D|True||||||||||||||||   #root|H-T-D|True||||||||||||||||   3. Delete the DTS members (for example as mentioned below) in the Period member hierarchy section,   D-T-D|True||||||||||||||||   W-T-D|True||||||||||||||||   M-T-D|True||||||||||||||||   Q-T-D|True||||||||||||||||   P-T-D|True||||||||||||||||   S-T-D|True||||||||||||||||   Y-T-D|True||||||||||||||||   H-T-D|True||||||||||||||||   4. Then save the edited Period dimension LCM artifact.   5. Then try to import the Period dimension using LCM.   6. Then Validate/Deploy the Planning application still the same issue. PS: This issue is fixed in 11.1.2.2.

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• The Product Owner

  - by Robert May

  In a previous post, I outlined the rules of Scrum.  This post details one of those rules. Picking a most important part of Scrum is difficult.  All of the rules are required, but if there were one rule that is “more” required that every other rule, its having a good Product Owner.  Simply put, the Product Owner can make or break the project. Duties of the Product Owner A Product Owner has many duties and responsibilities.  I’ll talk about each of these duties in detail below. A Product Owner: Discovers and records stories for the backlog. Prioritizes stories in the Product Backlog, Release Backlog and Iteration Backlog. Determines Release dates and Iteration Dates. Develops story details and helps the team understand those details. Helps QA to develop acceptance tests. Interact with the Customer to make sure that the product is meeting the customer’s needs. Discovers and Records Stories for the Backlog When I do Scrum, I always use User Stories as the means for capturing functionality that’s required in the system.  Some people will use Use Cases, but the same rule applies.  The Product Owner has the ultimate responsibility for figuring out what functionality will be in the system.  Many different mechanisms for capturing this input can be used.  User interviews are great, but all sources should be considered, including talking with Customer Support types.  Often, they hear what users are struggling with the most and are a great source for stories that can make the application easier to use. Care should be taken when soliciting user stories from technical types such as programmers and the people that manage them.  They will almost always give stories that are very technical in nature and may not have a direct benefit for the end user.  Stories are about adding value to the company.  If the stories don’t have direct benefit to the end user, the Product Owner should question whether or not the story should be implemented.  In general, technical stories should be included as tasks in User Stories.  Technical stories are often needed, but the ultimate value to the user is in user based functionality, so technical stories should be considered nothing more than overhead in providing that user functionality. Until the iteration prior to development, stories should be nothing more than short, one line placeholders. An exercise called Story Planning can be used to brainstorm and come up with stories.  I’ll save the description of this activity for another blog post. For more information on User Stories, please read the book User Stories Applied by Mike Cohn. Prioritizes Stories in the Product Backlog, Release Backlog and Iteration Backlog Prioritization of stories is one of the most difficult tasks that a Product Owner must do.  A key concept of Scrum done right is the need to have the team working from a single set of prioritized stories.  If the team does not have a single set of prioritized stories, Scrum will likely fail at your organization.  The Product Owner is the ONLY person who has the responsibility to prioritize that list.  The Product Owner must be very diplomatic and sincerely listen to the people around him so that he can get the priorities correct. Just listening will still not yield the proper priorities.  Care must also be taken to ensure that Return on Investment is also considered.  Ultimately, determining which stories give the most value to the company for the least cost is the most important factor in determining priorities.  Product Owners should be willing to look at cold, hard numbers to determine the order for stories.  Even when many people want a feature, if that features is costly to develop, it may not have as high of a return on investment as features that are cheaper, but not as popular. The act of prioritization often causes conflict in an environment.  Customer Service thinks that feature X is the most important, because it will stop people from calling.  Operations thinks that feature Y is the most important, because it will stop servers from crashing.  Developers think that feature Z is most important because it will make writing software much easier for them.  All of these are useful goals, but the team can have only one list of items, and each item must have a priority that is different from all other stories.  The Product Owner will determine which feature gives the best return on investment and the other features will have to wait their turn, which means that someone will not have their top priority feature implemented first. A weak Product Owner will refuse to do prioritization.  I’ve heard from multiple Product Owners the following phrase, “Well, it’s all got to be done, so what does it matter what order we do it in?”  If your product owner is using this phrase, you need a new Product Owner.  Order is VERY important.  In Scrum, every release is potentially shippable.  If the wrong priority items are developed, then the value added in each release isn’t what it should be.  Additionally, the Product Owner with this mindset doesn’t understand Agile.  A product is NEVER finished, until the company has decided that it is no longer a going concern and they are no longer going to sell the product.  Therefore, prioritization isn’t an event, its something that continues every day.  The logical extension of the phrase “It’s all got to be done” is that you will never ship your product, since a product is never “done.”  Once stories have been prioritized, assigning them to the Release Backlog and the Iteration Backlog becomes relatively simple.  The top priority items are copied into the respective backlogs in order and the task is complete.  The team does have the right to shuffle things around a little in the iteration backlog.  For example, they may determine that working on story C with story A is appropriate because they’re related, even though story B is technically a higher priority than story C.  Or they may decide that story B is too big to complete in the time available after Story A has tasks created, so they’ll work on Story C since it’s smaller.  They can’t, however, go deep into the backlog to pick stories to implement.  The team and the Product Owner should work together to determine what’s best for the company. Prioritization is time consuming, but its one of the most important things a Product Owner does. Determines Release Dates and Iteration Dates Product owners are responsible for determining release dates for a product.  A common misconception that Product Owners have is that every “release” needs to correspond with an actual release to customers.  This is not the case.  In general, releases should be no more than 3 months long.  You  may decide to release the product to the customers, and many companies do release the product to customers, but it may also be an internal release. If a release date is too far away, developers will fall into the trap of not feeling a sense of urgency.  The date is far enough away that they don’t need to give the release their full attention.  Additionally, important tasks, such as performance tuning, regression testing, user documentation, and release preparation, will not happen regularly, making them much more difficult and time consuming to do.  The more frequently you do these tasks, the easier they are to accomplish. The Product Owner will be a key participant in determining whether or not a release should be sent out to the customers.  The determination should be made on whether or not the features contained in the release are valuable enough  and complete enough that the customers will see real value in the release.  Often, some features will take more than three months to get them to a state where they qualify for a release or need additional supporting features to be released.  The product owner has the right to make this determination. In addition to release dates, the Product Owner also will help determine iteration dates.  In general, an iteration length should be chosen and the team should follow that iteration length for an extended period of time.  If the iteration length is changed every iteration, you’re not doing Scrum.  Iteration lengths help the team and company get into a rhythm of developing quality software.  Iterations should be somewhere between 2 and 4 weeks in length.  Any shorter, and significant software will likely not be developed.  Any longer, and the team won’t feel urgency and planning will become very difficult. Iterations may not be extended during the iteration.  Companies where Scrum isn’t really followed will often use this as a strategy to complete all stories.  They don’t want to face the harsh reality of what their true performance is, and looking good is more important than seeking visibility and improving the process and team.  Companies like this typically don’t allow failure.  This is unhealthy.  Failure is part of life and unless we learn from it, we can’t improve.  I would much rather see a team push out stories to the next iteration and then have healthy discussions about why they failed rather than extend the iteration and not deal with the core problems. If iteration length varies, retrospectives become more difficult.  For example, evaluating the performance of the team’s estimation efforts becomes much more difficult if the iteration length varies.  Also, the team must have a velocity measurement.  If the iteration length varies, measuring velocity becomes impossible and upper management no longer will have the ability to evaluate the teams performance.  People external to the team will no longer have the ability to determine when key features are likely to be developed.  Variable iterations cause the entire company to fail and likely cause Scrum to fail at an organization. Develops Story Details and Helps the Team Understand Those Details A key concept in Scrum is that the stories are nothing more than a placeholder for a conversation.  Stories should be nothing more than short, one line statements about the functionality.  The team will then converse with the Product Owner about the details about that story.  The product owner needs to have a very good idea about what the details of the story are and needs to be able to help the team understand those details. Too often, we see this requirement as being translated into the need for comprehensive documentation about the story, including old fashioned requirements documentation.  The team should only develop the documentation that is required and should not develop documentation that is only created because their is a process to do so. In general, what we see that works best is the iteration before a team starts development work on a story, the Product Owner, with other appropriate business analysts, will develop the details of that story.  They’ll figure out what business rules are required, potentially make paper prototypes or other light weight mock-ups, and they seek to understand the story and what is implied.  Note that the time allowed for this task is deliberately short.  The Product Owner only has a single iteration to develop all of the stories for the next iteration. If more than one iteration is used, I’ve found that teams will end up with Big Design Up Front and traditional requirements documents.  This is a waste of time, since the team will need to then have discussions with the Product Owner to figure out what the requirements document says.  Instead of this, skip making the pretty pictures and detailing the nuances of the requirements and build only what is minimally needed by the team to do development.  If something comes up during development, you can address it at that time and figure out what you want to do.  The goal is to keep things as light weight as possible so that everyone can move as quickly as possible. Helps QA to Develop Acceptance Tests In Scrum, no story can be counted until it is accepted by QA.  Because of this, acceptance tests are very important to the team.  In general, acceptance tests need to be developed prior to the iteration or at the very beginning of the iteration so that the team can make sure that the tasks that they develop will fulfill the acceptance criteria. The Product Owner will help the team, including QA, understand what will make the story acceptable.  Note that the Product Owner needs to be careful about specifying that the feature will work “Perfectly” at the end of the iteration.  In general, features are developed a little bit at a time, so only the bit that is being developed should be considered as necessary for acceptance. A weak Product Owner will make statements like “Do it right the first time.”  Not only are these statements damaging to the team (like they would try to do it WRONG the first time . . .), they’re also ignoring the iterative nature of Scrum.  Additionally, a weak product owner will seek to add scope in the acceptance testing.  For example, they will refuse to determine acceptance at the beginning of the iteration, and then, after the team has planned and committed to the iteration, they will expand scope by defining acceptance.  This often causes the team to miss the iteration because scope that wasn’t planned on is included.  There are ways that the team can mitigate this problem.  For example, include extra “Product Owner” time to deal with the uncertainty that you know will be introduced by the Product Owner.  This will slow the perceived velocity of the team and is not ideal, since they’ll be doing more work than they get credit for. Interact with the Customer to Make Sure that the Product is Meeting the Customer’s Needs Once development is complete, what the team has worked on should be put in front of real live people to see if it meets the needs of the customer.  One of the great things about Agile is that if something doesn’t work, we can revisit it in a future iteration!  This frees up the team to make the best decision now and know that if that decision proves to be incorrect, the team can revisit it and change that decision. Features are about adding value to the customer, so if the customer doesn’t find them useful, then having the team make tweaks is valuable.  In general, most software will be 80 to 90 percent “right” after the initial round and only minor tweaks are required.  If proper coding standards are followed, these tweaks are usually minor and easy to accomplish.  Product Owners that are doing a good job will encourage real users to see and use the software, since they know that they are trying to add value to the customer. Poor product owners will think that they know the answers already, that their customers are silly and do stupid things and that they don’t need customer input.  If you have a product owner that is afraid to show the team’s work to real customers, you probably need a different product owner. Up Next, “Who Makes a Good Product Owner.” Followed by, “Messing with the Team.” Technorati Tags: Scrum,Product Owner

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• Little PM side post...

  - by edgaralgernon

  When adding new team memebers... off set the ramp up time by 1) having pre built machines ready and and easy method of getting the lastest tools, code base etc. I'm fortunate enough to be at a client that has a machine ready built and loaded when the dev arrives, all they have to do is grab the code. 2) have tasks broken down so that dependencies are as minimal as possible. In other words, to over come the mythical man month issue (as recently mentioned on slashdot) make sure the tasks you hand out have few dependencies on each other. That way the new dev is able to be productive fairly quickly. Here's our historical lead time... the bump in Jan is due to added work, by 2/18 we had added 4 new people over the last two weeks. And amazing the time starts coming down: Here's our averag work time: again time ramps up as we are adding more tasks, but then starts inching back down through out Feb and March. It's not that we beat the Mythical Man Month, and in fact I still believe the book and idea are highly relevant. But if you can break the tasks down and reduce the dependencies between the task then you can mitigate the effect. The tool used in this case is from AgileZen.com and some of the wild swings are due to inexperience with the system initially... but our average times as measured by the tool are matching real life. Also the tool appearst to measure in 24 hour days and 7 day weeks. so it isn't as bad as it looks. :-)

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• How Oracle Data Integration Customers Differentiate Their Business in Competitive Markets

  - by Irem Radzik

  Normal 0 false false false EN-US X-NONE X-NONE MicrosoftInternetExplorer4 With data being a central force in driving innovation and competing effectively, data integration has become a key IT approach to remove silos and ensure working with consistent and trusted data. Especially with the release of 12c version, Oracle Data Integrator and Oracle GoldenGate offer easy-to-use and high-performance solutions that help companies with their critical data initiatives, including big data analytics, moving to cloud architectures, modernizing and connecting transactional systems and more. In a recent press release we announced the great momentum and analyst recognition Oracle Data Integration products have achieved in the data integration and replication market. In this press release we described some of the key new features of Oracle Data Integrator 12c and Oracle GoldenGate 12c. In addition, a few from our 4500+ customers explained how Oracle’s data integration platform helped them achieve their business goals. In this blog post I would like to go over what these customers shared about their experience. Land O’Lakes is one of America’s premier member-owned cooperatives, and offers an extensive line of agricultural supplies, as well as production and business services. Rich Bellefeuille, manager, ETL & data warehouse for Land O’Lakes told us how GoldenGate helped them modernize their critical ERP system without impacting service and how they are moving to new projects with Oracle Data Integrator 12c: “With Oracle GoldenGate 11g, we've been able to migrate our enterprise-wide implementation of Oracle’s JD Edwards EnterpriseOne, ERP system, to a new database and application server platform with minimal downtime to our business. Using Oracle GoldenGate 11g we reduced database migration time from nearly 30 hours to less than 30 minutes. Given our quick success, we are considering expansion of our Oracle GoldenGate 12c footprint. We are also in the midst of deploying a solution leveraging Oracle Data Integrator 12c to manage our pricing data to handle orders more effectively and provide a better relationship with our clients. We feel we are gaining higher productivity and flexibility with Oracle's data integration products." ICON, a global provider of outsourced development services to the pharmaceutical, biotechnology and medical device industries, highlighted the competitive advantage that a solid data integration foundation brings. Diarmaid O’Reilly, enterprise data warehouse manager, ICON plc said “Oracle Data Integrator enables us to align clinical trials intelligence with the information needs of our sponsors. It helps differentiate ICON’s services in an increasingly competitive drug-development industry."  You can find more info on ICON's implementation here. A popular use case for Oracle GoldenGate’s real-time data integration is offloading operational reporting from critical transaction processing systems. SolarWorld, one of the world’s largest solar-technology producers and the largest U.S. solar panel manufacturer, implemented Oracle GoldenGate for real-time data integration of manufacturing data for fast analysis. Russ Toyama, U.S. senior database administrator for SolarWorld told us real-time data helps their operations and GoldenGate’s solution supports high performance of their manufacturing systems: “We use Oracle GoldenGate for real-time data integration into our decision support system, which performs real-time analysis for manufacturing operations to continuously improve product quality, yield and efficiency. With reliable and low-impact data movement capabilities, Oracle GoldenGate also helps ensure that our critical manufacturing systems are stable and operate with high performance."  You can watch the full interview with SolarWorld's Russ Toyama here. Normal 0 false false false EN-US X-NONE X-NONE MicrosoftInternetExplorer4 /* Style Definitions */ table.MsoNormalTable {mso-style-name:"Table Normal"; mso-tstyle-rowband-size:0; mso-tstyle-colband-size:0; mso-style-noshow:yes; mso-style-priority:99; mso-style-qformat:yes; mso-style-parent:""; mso-padding-alt:0in 5.4pt 0in 5.4pt; mso-para-margin:0in; mso-para-margin-bottom:.0001pt; mso-pagination:widow-orphan; font-size:11.0pt; font-family:"Calibri","sans-serif"; mso-ascii-font-family:Calibri; mso-ascii-theme-font:minor-latin; mso-fareast-font-family:"Times New Roman"; mso-fareast-theme-font:minor-fareast; mso-hansi-font-family:Calibri; mso-hansi-theme-font:minor-latin; mso-bidi-font-family:"Times New Roman"; mso-bidi-theme-font:minor-bidi;} Starwood Hotels and Resorts is one of the many customers that found out how well Oracle Data Integration products work with Oracle Exadata. Gordon Light, senior director of information technology for StarWood Hotels, says they had notable performance gain in loading Oracle Exadata reporting environment: “We leverage Oracle GoldenGate to replicate data from our central reservations systems and other OLTP databases – significantly decreasing the overall ETL duration. Moving forward, we plan to use Oracle GoldenGate to help the company achieve near-real-time reporting.”You can listen about Starwood Hotels' implementation here. Many companies combine the power of Oracle GoldenGate with Oracle Data Integrator to have a single, integrated data integration platform for variety of use cases across the enterprise. Ufone is another good example of that. The leading mobile communications service provider of Pakistan has improved customer service using timely customer data in its data warehouse. Atif Aslam, head of management information systems for Ufone says: “Oracle Data Integrator and Oracle GoldenGate help us integrate information from various systems and provide up-to-date and real-time CRM data updates hourly, rather than daily. The applications have simplified data warehouse operations and allowed business users to make faster and better informed decisions to protect revenue in the fast-moving Pakistani telecommunications market.” You can read more about Ufone's use case here. In our Oracle Data Integration 12c launch webcast back in November we also heard from BT’s CTO Surren Parthab about their use of GoldenGate for moving to private cloud architecture. Surren also shared his perspectives on Oracle Data Integrator 12c and Oracle GoldenGate 12c releases. You can watch the video here. These are only a few examples of leading companies that have made data integration and real-time data access a key part of their data governance and IT modernization initiatives. They have seen real improvements in how their businesses operate and differentiate in today’s competitive markets. You can read about other customer examples in our Ebook: The Path to the Future and access resources including white papers, data sheets, podcasts and more via our Oracle Data Integration resource kit. /* Style Definitions */ table.MsoNormalTable {mso-style-name:"Table Normal"; mso-tstyle-rowband-size:0; mso-tstyle-colband-size:0; mso-style-noshow:yes; mso-style-priority:99; mso-style-qformat:yes; mso-style-parent:""; mso-padding-alt:0in 5.4pt 0in 5.4pt; mso-para-margin:0in; mso-para-margin-bottom:.0001pt; mso-pagination:widow-orphan; font-size:11.0pt; font-family:"Calibri","sans-serif"; mso-ascii-font-family:Calibri; mso-ascii-theme-font:minor-latin; mso-fareast-font-family:"Times New Roman"; mso-fareast-theme-font:minor-fareast; mso-hansi-font-family:Calibri; mso-hansi-theme-font:minor-latin; mso-bidi-font-family:"Times New Roman"; mso-bidi-theme-font:minor-bidi;}

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• C#: Adding Functionality to 3rd Party Libraries With Extension Methods

  - by James Michael Hare

  Ever have one of those third party libraries that you love but it's missing that one feature or one piece of syntactical candy that would make it so much more useful?  This, I truly think, is one of the best uses of extension methods.  I began discussing extension methods in my last post (which you find here) where I expounded upon what I thought were some rules of thumb for using extension methods correctly.  As long as you keep in line with those (or similar) rules, they can often be useful for adding that little extra functionality or syntactical simplification for a library that you have little or no control over. Oh sure, you could take an open source project, download the source and add the methods you want, but then every time the library is updated you have to re-add your changes, which can be cumbersome and error prone.  And yes, you could possibly extend a class in a third party library and override features, but that's only if the class is not sealed, static, or constructed via factories. This is the perfect place to use an extension method!  And the best part is, you and your development team don't need to change anything!  Simply add the using for the namespace the extensions are in! So let's consider this example.  I love log4net!  Of all the logging libraries I've played with, it, to me, is one of the most flexible and configurable logging libraries and it performs great.  But this isn't about log4net, well, not directly.  So why would I want to add functionality?  Well, it's missing one thing I really want in the ILog interface: ability to specify logging level at runtime. For example, let's say I declare my ILog instance like so:     using log4net;     public class LoggingTest     {         private static readonly ILog _log = LogManager.GetLogger(typeof(LoggingTest));         ...     }     If you don't know log4net, the details aren't important, just to show that the field _log is the logger I have gotten from log4net. So now that I have that, I can log to it like so:     _log.Debug("This is the lowest level of logging and just for debugging output.");     _log.Info("This is an informational message.  Usual normal operation events.");     _log.Warn("This is a warning, something suspect but not necessarily wrong.");     _log.Error("This is an error, some sort of processing problem has happened.");     _log.Fatal("Fatals usually indicate the program is dying hideously."); And there's many flavors of each of these to log using string formatting, to log exceptions, etc.  But one thing there isn't: the ability to easily choose the logging level at runtime.  Notice, the logging levels above are chosen at compile time.  Of course, you could do some fun stuff with lambdas and wrap it, but that would obscure the simplicity of the interface.  And yes there is a Logger property you can dive down into where you can specify a Level, but the Level properties don't really match the ILog interface exactly and then you have to manually build a LogEvent and... well, it gets messy.  I want something simple and sexy so I can say:     _log.Log(someLevel, "This will be logged at whatever level I choose at runtime!");     Now, some purists out there might say you should always know what level you want to log at, and for the most part I agree with them.  For the most party the ILog interface satisfies 99% of my needs.  In fact, for most application logging yes you do always know the level you will be logging at, but when writing a utility class, you may not always know what level your user wants. I'll tell you, one of my favorite things is to write reusable components.  If I had my druthers I'd write framework libraries and shared components all day!  And being able to easily log at a runtime-chosen level is a big need for me.  After all, if I want my code to really be re-usable, I shouldn't force a user to deal with the logging level I choose. One of my favorite uses for this is in Interceptors -- I'll describe Interceptors in my next post and some of my favorites -- for now just know that an Interceptor wraps a class and allows you to add functionality to an existing method without changing it's signature.  At the risk of over-simplifying, it's a very generic implementation of the Decorator design pattern. So, say for example that you were writing an Interceptor that would time method calls and emit a log message if the method call execution time took beyond a certain threshold of time.  For instance, maybe if your database calls take more than 5,000 ms, you want to log a warning.  Or if a web method call takes over 1,000 ms, you want to log an informational message.  This would be an excellent use of logging at a generic level. So here was my personal wish-list of requirements for my task: Be able to determine if a runtime-specified logging level is enabled. Be able to log generically at a runtime-specified logging level. Have the same look-and-feel of the existing Debug, Info, Warn, Error, and Fatal calls.    Having the ability to also determine if logging for a level is on at runtime is also important so you don't spend time building a potentially expensive logging message if that level is off.  Consider an Interceptor that may log parameters on entrance to the method.  If you choose to log those parameter at DEBUG level and if DEBUG is not on, you don't want to spend the time serializing those parameters. Now, mine may not be the most elegant solution, but it performs really well since the enum I provide all uses contiguous values -- while it's never guaranteed, contiguous switch values usually get compiled into a jump table in IL which is VERY performant - O(1) - but even if it doesn't, it's still so fast you'd never need to worry about it. So first, I need a way to let users pass in logging levels.  Sure, log4net has a Level class, but it's a class with static members and plus it provides way too many options compared to ILog interface itself -- and wouldn't perform as well in my level-check -- so I define an enum like below.     namespace Shared.Logging.Extensions     {         // enum to specify available logging levels.         public enum LoggingLevel         {             Debug,             Informational,             Warning,             Error,             Fatal         }     } Now, once I have this, writing the extension methods I need is trivial.  Once again, I would typically /// comment fully, but I'm eliminating for blogging brevity:     namespace Shared.Logging.Extensions     {         // the extension methods to add functionality to the ILog interface         public static class LogExtensions         {             // Determines if logging is enabled at a given level.             public static bool IsLogEnabled(this ILog logger, LoggingLevel level)             {                 switch (level)                 {                     case LoggingLevel.Debug:                         return logger.IsDebugEnabled;                     case LoggingLevel.Informational:                         return logger.IsInfoEnabled;                     case LoggingLevel.Warning:                         return logger.IsWarnEnabled;                     case LoggingLevel.Error:                         return logger.IsErrorEnabled;                     case LoggingLevel.Fatal:                         return logger.IsFatalEnabled;                 }                                 return false;             }             // Logs a simple message - uses same signature except adds LoggingLevel             public static void Log(this ILog logger, LoggingLevel level, object message)             {                 switch (level)                 {                     case LoggingLevel.Debug:                         logger.Debug(message);                         break;                     case LoggingLevel.Informational:                         logger.Info(message);                         break;                     case LoggingLevel.Warning:                         logger.Warn(message);                         break;                     case LoggingLevel.Error:                         logger.Error(message);                         break;                     case LoggingLevel.Fatal:                         logger.Fatal(message);                         break;                 }             }             // Logs a message and exception to the log at specified level.             public static void Log(this ILog logger, LoggingLevel level, object message, Exception exception)             {                 switch (level)                 {                     case LoggingLevel.Debug:                         logger.Debug(message, exception);                         break;                     case LoggingLevel.Informational:                         logger.Info(message, exception);                         break;                     case LoggingLevel.Warning:                         logger.Warn(message, exception);                         break;                     case LoggingLevel.Error:                         logger.Error(message, exception);                         break;                     case LoggingLevel.Fatal:                         logger.Fatal(message, exception);                         break;                 }             }             // Logs a formatted message to the log at the specified level.              public static void LogFormat(this ILog logger, LoggingLevel level, string format,                                          params object[] args)             {                 switch (level)                 {                     case LoggingLevel.Debug:                         logger.DebugFormat(format, args);                         break;                     case LoggingLevel.Informational:                         logger.InfoFormat(format, args);                         break;                     case LoggingLevel.Warning:                         logger.WarnFormat(format, args);                         break;                     case LoggingLevel.Error:                         logger.ErrorFormat(format, args);                         break;                     case LoggingLevel.Fatal:                         logger.FatalFormat(format, args);                         break;                 }             }         }     } So there it is!  I didn't have to modify the log4net source code, so if a new version comes out, i can just add the new assembly with no changes.  I didn't have to subclass and worry about developers not calling my sub-class instead of the original.  I simply provide the extension methods and it's as if the long lost extension methods were always a part of the ILog interface! Consider a very contrived example using the original interface:     // using the original ILog interface     public class DatabaseUtility     {         private static readonly ILog _log = LogManager.Create(typeof(DatabaseUtility));                 // some theoretical method to time         IDataReader Execute(string statement)         {             var timer = new System.Diagnostics.Stopwatch();                         // do DB magic                                    // this is hard-coded to warn, if want to change at runtime tough luck!             if (timer.ElapsedMilliseconds > 5000 && _log.IsWarnEnabled)             {                 _log.WarnFormat("Statement {0} took too long to execute.", statement);             }             ...         }     }     Now consider this alternate call where the logging level could be perhaps a property of the class          // using the original ILog interface     public class DatabaseUtility     {         private static readonly ILog _log = LogManager.Create(typeof(DatabaseUtility));                 // allow logging level to be specified by user of class instead         public LoggingLevel ThresholdLogLevel { get; set; }                 // some theoretical method to time         IDataReader Execute(string statement)         {             var timer = new System.Diagnostics.Stopwatch();                         // do DB magic                                    // this is hard-coded to warn, if want to change at runtime tough luck!             if (timer.ElapsedMilliseconds > 5000 && _log.IsLogEnabled(ThresholdLogLevel))             {                 _log.LogFormat(ThresholdLogLevel, "Statement {0} took too long to execute.",                     statement);             }             ...         }     } Next time, I'll show one of my favorite uses for these extension methods in an Interceptor.

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• Free SQL Server training? Now you’re talking.

  - by Fatherjack

  SQL Server user groups are everywhere, literally all over the globe there are SQL Server professionals meeting on a regular basis, sharing ideas, solving problems, learning about how to do new stuff and new ways to do old stuff and it’s all for free. I don’t have detailed figures but of all the SQL Server professionals there are only a small number of them attend these user groups. Those people are the people that are taking the time and making then effort to make themselves better at their chosen trade, more employable and having a good time. For free. I don’t know why but there are many people that don’t seem to want to be the best they can be. Some of you enlightened people that do already attend could be doing more though. Have you ever spoken at  your group? Not just in the break while you have a mouthful of pizza and a drink in your hand but had the attention of the whole group listen to you speak. It doesn’t need to be a full hour, it doesn’t need to be some obscure deeply technical demonstration of SQL Server internals, just a few minutes on something that you do that might help other people with their daily work. A neat process that helps you get from Problem A to Solution B. There is no need to get concerned that becoming a speaker means that you suddenly have to know more than anyone else in the room. This is you talking about something that you experienced. What you did, what you would repeat, what you might do differently next time. No one in the audience can pick you up on a technicality. If someone comes out with a great idea that you hadn’t thought of, say “That’s a great idea, I didn’t think of that while we had the problem on our hands. I’ll try to remember that for next time”. If someone is looking to show you up for picking the wrong decision (and this, in my experience, is very uncommon indeed) then you simply give a reply like “Well, at the time we chose that option. Perhaps another time then we would tackle things differently but we were happy with how our solution worked”. It’s sharing things like this that makes user groups have a real value, talking about how you coped with or averted a disaster, a handy little section of code or using a tool in a particular way that you take for granted that might, just might, be something that other people haven’t thought of that solves a problem or saves some time for them. At the next meeting you might get the same benefit from a different person and so it goes on. As individuals benefits so the community benefits. For free. Things I encourage you to do; If you are a chapter or user group leader; encourage someone from your group who has never spoken before to start speaking. If you are a chapter or user group attendee that hasn’t spoken before; speak for at least 5 minutes on something related to SQL Server at any group meeting. If you don’t currently attend a user group; please go along to you nearest one when they are meeting next and invest in yourself and your future. UK user group details are here: http://sqlsouthwest.co.uk/national_ug.htm , PASS chapters outside the UK are found via http://www.sqlpass.org/PASSChapters/LocalChapters.aspx. If you are unsure of how you might achieve any of these things then get in touch with me*, I’ll give you specific advice on getting started on any of the above points and help you prove to yourself what you are capable of. SQL Community – be part of it and make it better. Let me know how you get on in the comments.

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• SQL SERVER – What is SSRS and Why SSRS is asked for in many Job Opening?

  - by Pinal Dave

  This example is from the Beginning SSRS by Kathi Kellenberger. Supporting files are available with a free download from the www.Joes2Pros.com web site. This will be a 5 day blog post in getting started with SSRS. Today will show the importance of SSRS in the business. Why is SSRS asked for in so many job openings? If you talk to an SSRS expert it’s very clear to them exactly why companies really need this invention and how it saves time and adds business value. You don’t have to be an SSRS expert to know its value or to start using it. For example you don’t have to be an airline pilot to know the usefulness of modern transportation. Even the people who don’t know how to run SSRS but need the reports can tell you why that is needed. This blog post will go into why SSRS is an important invention by showing how it improves the usage of information in your company. Before SSRS there has always been a need for a company to benefit from the use of its own information. Excel spreadsheets have been a popular way to do this for a long time. With SSRS you can still use this solution and gain many other options too. A friend of mine told me a story about doing database work in the 90s for a major company and how he wished SSRS was available back then. The Vice President of the marketing channel would often come to him just before an important meeting with the board of directors. He often needed to show how certain product sales were performing over time. All this information was in the database so it was my friend’s job to get the information out and organized into a medium the VP could use. This medium was usually Excel. The VP often had meetings all over the world where he showcased this Excel report. The solution to get the VP to him anywhere he was in the world was an Excel file attached to an e-mail. This worked pretty well but with some drawbacks. One time my friend sent the wrong file in the e-mail. A few minutes later my friend realized his mistake and sent another frantic e-mail to VP. This one was saying to ignore the last e-mail and use this newer one. Would the VP see the correct e-mail in time? If SSRS had been available, my friend could have created a solution that let the VP run the report any time he wished. The report could have been published to the company intranet where the VP could run it from any of the offices he happened to be traveling to that month. There is a fair amount of work up front to develop and publish the report, but once that work is completed, the report can be reused as many times as needed. My friend could even be on vacation for the first day of the monthly and the VP can get his real-time report. Not only could the report show the most recent data, the VP could choose to view reports of previous months with just a few clicks. The deployed SSRS is user friendly, and can also be configured to protect reports from being run by the wrong people. Tomorrow’s Post Tomorrow’s blog post will show how to know if you already have SSRS installed. If you want to learn SSRS in easy to simple words – I strongly recommend you to get Beginning SSRS book from Joes 2 Pros. Reference: Pinal Dave (http://blog.sqlauthority.com) Filed under: PostADay, SQL, SQL Authority, SQL Query, SQL Server, SQL Tips and Tricks, T SQL Tagged: Reporting Services, SSRS

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• Creating A SharePoint Parent/Child List Relationship&ndash; SharePoint 2010 Edition

  - by Mark Rackley

  Hey blog readers… It has been almost 2 years since I posted my most read blog on creating a Parent/Child list relationship in SharePoint 2007: Creating a SharePoint List Parent / Child Relationship - Out of the Box And then a year ago I improved on my method and redid the blog post… still for SharePoint 2007: Creating a SharePoint List Parent/Child Relationship – VIDEO REMIX Since then many of you have been asking me how to get this to work in SharePoint 2010, and frankly I have just not had time to look into it. I wish I could have jumped into this sooner, but have just recently began to look at it. Well.. after all this time I have actually come up with two solutions that work, neither of them are as clean as I’d like them to be, but I wanted to get something in your hands that you can start using today. Hopefully in the coming weeks and months I’ll be able to improve upon this further and give you guys some better options. For the most part, the process is identical to the 2007 process, but you have probably found out that the list view web parts in 2010 behave differently, and getting the Parent ID to your new child form can be a pain in the rear (at least that’s what I’ve discovered). Anyway, like I said, I have found a couple of solutions that work. If you know of a better one, please let us know as it bugs me that this not as eloquent as my 2007 implementation. Getting on the same page First thing I’d recommend is recreating this blog: Creating a SharePoint List Parent/Child Relationship – VIDEO REMIX in SharePoint 2010… There are some vague differences, but it’s basically the same…  Here’s a quick video of me doing this in SP 2010: Creating Lists necessary for this blog post Now that you have the lists created, lets set up the New Time form to use a QueryString variable to populate the Parent ID field: Creating parameters in Child’s new item form to set parent ID Did I talk fast enough through both of those videos? Hopefully by now that stuff is old hat to you, but I wanted to make sure everyone could get on the same page.  Okay… let’s get started. Solution 1 – XSLTListView with Javascript This solution is the more elegant of the two, however it does require the use of a little javascript.  The other solution does not use javascript, but it also doesn’t use the pretty new SP 2010 pop-ups.  I’ll let you decide which you like better. The basic steps of this solution are: Inserted a Related Item View Insert a ContentEditorWebPart Insert script in ContentEditorWebPart that pulls the ID from the Query string and calls the method to insert a new item on the child entry form Hide the toolbar from data view to remove “add new item” link. Again, you don’t HAVE to use a CEWP, you could just put the javascript directly in the page using SPD.  Anyway, here is how I did it: Using Related Item View / JavaScript Here’s the JavaScript I used in my Content Editor Web Part: <script type="text/javascript"> function NewTime() { // Get the Query String values and split them out into the vals array var vals = new Object(); var qs = location.search.substring(1, location.search.length); var args = qs.split("&"); for (var i=0; i < args.length; i++) { var nameVal = args[i].split("="); var temp = unescape(nameVal[1]).split('+'); nameVal[1] = temp.join(' '); vals[nameVal[0]] = nameVal[1]; } var issueID = vals["ID"]; //use this to bring up the pretty pop up NewItem2(event,"http://sp2010dev:1234/Lists/Time/NewForm.aspx?IssueID=" + issueID); //use this to open a new window //window.location="http://sp2010dev:1234/Lists/Time/NewForm.aspx?IssueID=" + issueID; } </script> Solution 2 – DataFormWebPart and exact same 2007 Process This solution is a little more of a hack, but it also MUCH more close to the process we did in SP 2007. So, if you don’t mind not having the pretty pop-up and prefer the comforts of what you are used to, you can give this one a try.  The basics steps are: Insert a DataFormWebPart instead of the List Data View Create a Parameter on DataFormWebPart to store “ID” Query String Variable Filter DataFormWebPart using Parameter Insert a link at bottom of DataForm Web part that points to the Child’s new item form and passes in the Parent Id using the Parameter. See.. like I told you, exact same process as in 2007 (except using the DataFormWeb Part). The DataFormWebPart also requires a lot more work to make it look “pretty” but it’s just table rows and cells, and can be configured pretty painlessly.  Here is that video: Using DataForm Web Part One quick update… if you change the link in this solution from: <tr> <td><a href="http://sp2010dev:1234/Lists/Time/NewForm.aspx?IssueID={$IssueIDParam}">Click here to create new item...</a> </td> </tr> to: <tr> <td> <a href="javascript:NewItem2(event,'http://sp2010dev:1234/Lists/Time/NewForm.aspx?IssueID={$IssueIDParam}');">Click here to create new item...</a> </td> </tr> It will open up in the pretty pop up and act the same as solution one… So… both Solutions will now behave the same to the end user. Just depends on which you want to implement. That’s all for now… Remember in both solutions when you have them working, you can make the “IssueID” invisible to users by using the “ms-hidden” class (it’s my previous blog post on the subject up there). That’s basically all there is to it! No pithy or witty closing this time… I am sorry it took me so long to dive into this and I hope your questions are answered. As I become more polished myself I will try to come up with a cleaner solution that will make everyone happy… As always, thanks for taking the time to stop by.

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• exporting bind and keyframe bone poses from blender to use in OpenGL

  - by SaldaVonSchwartz

  I'm having a hard time trying to understand how exactly Blender's concept of bone transforms maps to the usual math of skinning (which I'm implementing in an OpenGL-based engine of sorts). Or I'm missing out something in the math.. It's gonna be long, but here's as much background as I can think of. First, a few notes and assumptions: I'm using column-major order and multiply from right to left. So for instance, vertex v transformed by matrix A and then further transformed by matrix B would be: v' = BAv. This also means whenever I export a matrix from blender through python, I export it (in text format) in 4 lines, each representing a column. This is so I can then I can read them back into my engine like this: if (fscanf(fileHandle, "%f %f %f %f", &skeleton.joints[currentJointIndex].inverseBindTransform.m[0], &skeleton.joints[currentJointIndex].inverseBindTransform.m[1], &skeleton.joints[currentJointIndex].inverseBindTransform.m[2], &skeleton.joints[currentJointIndex].inverseBindTransform.m[3])) { if (fscanf(fileHandle, "%f %f %f %f", &skeleton.joints[currentJointIndex].inverseBindTransform.m[4], &skeleton.joints[currentJointIndex].inverseBindTransform.m[5], &skeleton.joints[currentJointIndex].inverseBindTransform.m[6], &skeleton.joints[currentJointIndex].inverseBindTransform.m[7])) { if (fscanf(fileHandle, "%f %f %f %f", &skeleton.joints[currentJointIndex].inverseBindTransform.m[8], &skeleton.joints[currentJointIndex].inverseBindTransform.m[9], &skeleton.joints[currentJointIndex].inverseBindTransform.m[10], &skeleton.joints[currentJointIndex].inverseBindTransform.m[11])) { if (fscanf(fileHandle, "%f %f %f %f", &skeleton.joints[currentJointIndex].inverseBindTransform.m[12], &skeleton.joints[currentJointIndex].inverseBindTransform.m[13], &skeleton.joints[currentJointIndex].inverseBindTransform.m[14], &skeleton.joints[currentJointIndex].inverseBindTransform.m[15])) { I'm simplifying the code I show because otherwise it would make things unnecessarily harder (in the context of my question) to explain / follow. Please refrain from making remarks related to optimizations. This is not final code. Having said that, if I understand correctly, the basic idea of skinning/animation is: I have a a mesh made up of vertices I have the mesh model-world transform W I have my joints, which are really just transforms from each joint's space to its parent's space. I'll call these transforms Bj meaning matrix which takes from joint j's bind pose to joint j-1's bind pose. For each of these, I actually import their inverse to the engine, Bj^-1. I have keyframes each containing a set of current poses Cj for each joint J. These are initially imported to my engine in TQS format but after (S)LERPING them I compose them into Cj matrices which are equivalent to the Bjs (not the Bj^-1 ones) only that for the current spacial configurations of each joint at that frame. Given the above, the "skeletal animation algorithm is" On each frame: check how much time has elpased and compute the resulting current time in the animation, from 0 meaning frame 0 to 1, meaning the end of the animation. (Oh and I'm looping forever so the time is mod(total duration)) for each joint: 1 -calculate its world inverse bind pose, that is Bj_w^-1 = Bj^-1 Bj-1^-1 ... B0^-1 2 -use the current animation time to LERP the componets of the TQS and come up with an interpolated current pose matrix Cj which should transform from the joints current configuration space to world space. Similar to what I did to get the world version of the inverse bind poses, I come up with the joint's world current pose, Cj_w = C0 C1 ... Cj 3 -now that I have world versions of Bj and Cj, I store this joint's world- skinning matrix K_wj = Cj_w Bj_w^-1. The above is roughly implemented like so: - (void)update:(NSTimeInterval)elapsedTime { static double time = 0; time = fmod((time + elapsedTime),1.); uint16_t LERPKeyframeNumber = 60 * time; uint16_t lkeyframeNumber = 0; uint16_t lkeyframeIndex = 0; uint16_t rkeyframeNumber = 0; uint16_t rkeyframeIndex = 0; for (int i = 0; i < aClip.keyframesCount; i++) { uint16_t keyframeNumber = aClip.keyframes[i].number; if (keyframeNumber <= LERPKeyframeNumber) { lkeyframeIndex = i; lkeyframeNumber = keyframeNumber; } else { rkeyframeIndex = i; rkeyframeNumber = keyframeNumber; break; } } double lTime = lkeyframeNumber / 60.; double rTime = rkeyframeNumber / 60.; double blendFactor = (time - lTime) / (rTime - lTime); GLKMatrix4 bindPosePalette[aSkeleton.jointsCount]; GLKMatrix4 currentPosePalette[aSkeleton.jointsCount]; for (int i = 0; i < aSkeleton.jointsCount; i++) { F3DETQSType& lPose = aClip.keyframes[lkeyframeIndex].skeletonPose.jointPoses[i]; F3DETQSType& rPose = aClip.keyframes[rkeyframeIndex].skeletonPose.jointPoses[i]; GLKVector3 LERPTranslation = GLKVector3Lerp(lPose.t, rPose.t, blendFactor); GLKQuaternion SLERPRotation = GLKQuaternionSlerp(lPose.q, rPose.q, blendFactor); GLKVector3 LERPScaling = GLKVector3Lerp(lPose.s, rPose.s, blendFactor); GLKMatrix4 currentTransform = GLKMatrix4MakeWithQuaternion(SLERPRotation); currentTransform = GLKMatrix4Multiply(currentTransform, GLKMatrix4MakeTranslation(LERPTranslation.x, LERPTranslation.y, LERPTranslation.z)); currentTransform = GLKMatrix4Multiply(currentTransform, GLKMatrix4MakeScale(LERPScaling.x, LERPScaling.y, LERPScaling.z)); if (aSkeleton.joints[i].parentIndex == -1) { bindPosePalette[i] = aSkeleton.joints[i].inverseBindTransform; currentPosePalette[i] = currentTransform; } else { bindPosePalette[i] = GLKMatrix4Multiply(aSkeleton.joints[i].inverseBindTransform, bindPosePalette[aSkeleton.joints[i].parentIndex]); currentPosePalette[i] = GLKMatrix4Multiply(currentPosePalette[aSkeleton.joints[i].parentIndex], currentTransform); } aSkeleton.skinningPalette[i] = GLKMatrix4Multiply(currentPosePalette[i], bindPosePalette[i]); } } At this point, I should have my skinning palette. So on each frame in my vertex shader, I do: uniform mat4 modelMatrix; uniform mat4 projectionMatrix; uniform mat3 normalMatrix; uniform mat4 skinningPalette[6]; attribute vec4 position; attribute vec3 normal; attribute vec2 tCoordinates; attribute vec4 jointsWeights; attribute vec4 jointsIndices; varying highp vec2 tCoordinatesVarying; varying highp float lIntensity; void main() { vec3 eyeNormal = normalize(normalMatrix * normal); vec3 lightPosition = vec3(0., 0., 2.); lIntensity = max(0.0, dot(eyeNormal, normalize(lightPosition))); tCoordinatesVarying = tCoordinates; vec4 skinnedVertexPosition = vec4(0.); for (int i = 0; i < 4; i++) { skinnedVertexPosition += jointsWeights[i] * skinningPalette[int(jointsIndices[i])] * position; } gl_Position = projectionMatrix * modelMatrix * skinnedVertexPosition; } The result: The mesh parts that are supposed to animate do animate and follow the expected motion, however, the rotations are messed up in terms of orientations. That is, the mesh is not translated somewhere else or scaled in any way, but the orientations of rotations seem to be off. So a few observations: In the above shader notice I actually did not multiply the vertices by the mesh modelMatrix (the one which would take them to model or world or global space, whichever you prefer, since there is no parent to the mesh itself other than "the world") until after skinning. This is contrary to what I implied in the theory: if my skinning matrix takes vertices from model to joint and back to model space, I'd think the vertices should already be premultiplied by the mesh transform. But if I do so, I just get a black screen. As far as exporting the joints from Blender, my python script exports for each armature bone in bind pose, it's matrix in this way: def DFSJointTraversal(file, skeleton, jointList): for joint in jointList: poseJoint = skeleton.pose.bones[joint.name] jointTransform = poseJoint.matrix.inverted() file.write('Joint ' + joint.name + ' Transform {\n') for col in jointTransform.col: file.write('{:9f} {:9f} {:9f} {:9f}\n'.format(col[0], col[1], col[2], col[3])) DFSJointTraversal(file, skeleton, joint.children) file.write('}\n') And for current / keyframe poses (assuming I'm in the right keyframe): def exportAnimations(filepath): # Only one skeleton per scene objList = [object for object in bpy.context.scene.objects if object.type == 'ARMATURE'] if len(objList) == 0: return elif len(objList) > 1: return #raise exception? dialog box? skeleton = objList[0] jointNames = [bone.name for bone in skeleton.data.bones] for action in bpy.data.actions: # One animation clip per action in Blender, named as the action animationClipFilePath = filepath[0 : filepath.rindex('/') + 1] + action.name + ".aClip" file = open(animationClipFilePath, 'w') file.write('target skeleton: ' + skeleton.name + '\n') file.write('joints count: {:d}'.format(len(jointNames)) + '\n') skeleton.animation_data.action = action keyframeNum = max([len(fcurve.keyframe_points) for fcurve in action.fcurves]) keyframes = [] for fcurve in action.fcurves: for keyframe in fcurve.keyframe_points: keyframes.append(keyframe.co[0]) keyframes = set(keyframes) keyframes = [kf for kf in keyframes] keyframes.sort() file.write('keyframes count: {:d}'.format(len(keyframes)) + '\n') for kfIndex in keyframes: bpy.context.scene.frame_set(kfIndex) file.write('keyframe: {:d}\n'.format(int(kfIndex))) for i in range(0, len(skeleton.data.bones)): file.write('joint: {:d}\n'.format(i)) joint = skeleton.pose.bones[i] jointCurrentPoseTransform = joint.matrix translationV = jointCurrentPoseTransform.to_translation() rotationQ = jointCurrentPoseTransform.to_3x3().to_quaternion() scaleV = jointCurrentPoseTransform.to_scale() file.write('T {:9f} {:9f} {:9f}\n'.format(translationV[0], translationV[1], translationV[2])) file.write('Q {:9f} {:9f} {:9f} {:9f}\n'.format(rotationQ[1], rotationQ[2], rotationQ[3], rotationQ[0])) file.write('S {:9f} {:9f} {:9f}\n'.format(scaleV[0], scaleV[1], scaleV[2])) file.write('\n') file.close() Which I believe follow the theory explained at the beginning of my question. But then I checked out Blender's directX .x exporter for reference.. and what threw me off was that in the .x script they are exporting bind poses like so (transcribed using the same variable names I used so you can compare): if joint.parent: jointTransform = poseJoint.parent.matrix.inverted() else: jointTransform = Matrix() jointTransform *= poseJoint.matrix and exporting current keyframe poses like this: if joint.parent: jointCurrentPoseTransform = joint.parent.matrix.inverted() else: jointCurrentPoseTransform = Matrix() jointCurrentPoseTransform *= joint.matrix why are they using the parent's transform instead of the joint in question's? isn't the join transform assumed to exist in the context of a parent transform since after all it transforms from this joint's space to its parent's? Why are they concatenating in the same order for both bind poses and keyframe poses? If these two are then supposed to be concatenated with each other to cancel out the change of basis? Anyway, any ideas are appreciated.

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• Not to miss! Today’s web seminar on content integration with Oracle Apps

  - by Lance Shaw

  Hello everyone.  The first web seminar in a three-part series kicks off later today, focused on the value of delivering and controlling the flow of content in the context of your most critical business applications.   If you are using Oracle E-Business Suite, PeopleSoft Enterprise, JD Edwards EnterpriseOne or Siebel CRM, we heartily recommend you investigate the value of centralizing the delivery of scanned images, forms, faxes and digital documents within those processes.  The improvements in efficiency and productivity can result in some impressive cost savings. One customer recently reported that they had realized an impressive ROI of 180% and that the investment in this new technology had paid for itself in a mere 6 months.  We hope you can spare some time today to join us at 1pm Eastern Time / 10am Pacific Time / 18:00 GMT. We think you will find it time well spent.   Click here to attend.  We look forward to seeing you there!

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• Glibc importance of error ...

  - by Oz123

  Hi Everyone, I am following LFS 6.7, and I reached the point where I compile glibc-2.12.1 . I mounted the LFS partition with the atime option: here is a confirm on that I think: /dev/sdb1 on /mnt /lfs type ext4 (rw) I get the following errors on making the test, and I have no clue if I should try to resolve them, or just ignore them and go on ... rpc/types.h sunrpc/rpc/svc_auth.h sunrpc/rpcsvc/bootparam.h sysvipc/sys/ipc.h \ sysvipc/sys/msg.h sysvipc/sys/sem.h sysvipc/sys/shm.h termios/termios.h \ termios/sys/termios.h termios/sys/ttychars.h time/time.h time/sys/time.h \ time/sys/timeb.h wcsmbs/wchar.h wctype/wctype.h > \ /sources/glibc-build/begin-end-check.out make[1]: Target `check' not remade because of errors. make[1]: Leaving directory `/sources/glibc-2.12.1' make: *** [check] Error 2 root:/sources/glibc-build# grep Error glibc-check-log make[2]: *** [/sources/glibc-build/math/test-float.out] Error 1 make[2]: *** [/sources/glibc-build/math/test-ifloat.out] Error 1 make[1]: *** [math/tests] Error 2 make[2]: [/sources/glibc-build/posix/annexc.out] Error 1 (ignored) make: *** [check] Error 2 thanks in advance, Oz

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• SQL SERVER – Maximize Database Performance with DB Optimizer – SQL in Sixty Seconds #054

  - by Pinal Dave

  Performance tuning is an interesting concept and everybody evaluates it differently. Every developer and DBA have different opinion about how one can do performance tuning. I personally believe performance tuning is a three step process Understanding the Query Identifying the Bottleneck Implementing the Fix While, we are working with large database application and it suddenly starts to slow down. We are all under stress about how we can get back the database back to normal speed. Most of the time we do not have enough time to do deep analysis of what is going wrong as well what will fix the problem. Our primary goal at that time is to just fix the database problem as fast as we can. However, here is one very important thing which we need to keep in our mind is that when we do quick fix, it should not create any further issue with other parts of the system. When time is essence and we want to do deep analysis of our system to give us the best solution we often tend to make mistakes. Sometimes we make mistakes as we do not have proper time to analysis the entire system. Here is what I do when I face such a situation – I take the help of DB Optimizer. It is a fantastic tool and does superlative performance tuning of the system. Everytime when I talk about performance tuning tool, the initial reaction of the people is that they do not want to try this as they believe it requires lots of the learning of the tool before they use it. It is absolutely not true with the case of the DB optimizer. It is a very easy to use and self intuitive tool. Once can get going with the product, in no time. Here is a quick video I have build where I demonstrate how we can identify what index is missing for query and how we can quickly create the index. Entire three steps of the query tuning are completed in less than 60 seconds. If you are into performance tuning and query optimization you should download DB Optimizer and give it a go. Let us see the same concept in following SQL in Sixty Seconds Video: You can Download DB Optimizer and reproduce the same Sixty Seconds experience. Related Tips in SQL in Sixty Seconds: Performance Tuning – Part 1 of 2 – Getting Started and Configuration Performance Tuning – Part 2 of 2 – Analysis, Detection, Tuning and Optimizing What would you like to see in the next SQL in Sixty Seconds video? Reference: Pinal Dave (http://blog.sqlauthority.com) Filed under: Database, Pinal Dave, PostADay, SQL, SQL Authority, SQL in Sixty Seconds, SQL Interview Questions and Answers, SQL Query, SQL Scripts, SQL Server, SQL Tips and Tricks, T SQL, Technology, Video Tagged: Identity

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• Friday Fun: Vehicles

  - by Mysticgeek

  Friday has finally arrived and it’s time to ignore spreadsheets and TPS reports and waste time playing a flash game. Today we take a look at the fun puzzle game called Vehicles. Vehicles This is a fun game with cartoon style graphics where you navigate vehicles to solve different puzzles. You navigate the vehicles through different puzzle situations by clicking on them with your mouse. You’re given basic instructions on how to complete each level. You’ll need to strategically place the vehicles so you can knock the black vehicles off the screen. As you progress up the levels, they become more challenging and if you need to, you can restart it at any time. Since it’s Friday, and you’re sick of your job, Vehicles is a fun puzzle game to keep your mind of the boringness of work until it’s time for weekend freedom. Play Vehicles at FreeWebArcade Similar Articles Productive Geek Tips Friday Fun: Relieve Workweek Frustration Playing Mad MondayFriday Fun: Uphill RushFriday Fun: Battlefield HeroesFriday Fun: Portal, the Flash VersionFriday Fun: Play 3D Rally Racing in Google Chrome TouchFreeze Alternative in AutoHotkey The Icy Undertow Desktop Windows Home Server – Backup to LAN The Clear & Clean Desktop Use This Bookmarklet to Easily Get Albums Use AutoHotkey to Assign a Hotkey to a Specific Window Latest Software Reviews Tinyhacker Random Tips VMware Workstation 7 Acronis Online Backup DVDFab 6 Revo Uninstaller Pro FetchMp3 Can Download Videos & Convert Them to Mp3 Use Flixtime To Create Video Slideshows Creating a Password Reset Disk in Windows Bypass Waiting Time On Customer Service Calls With Lucyphone MELTUP – "The Beginning Of US Currency Crisis And Hyperinflation" Enable or Disable the Task Manager Using TaskMgrED

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• ORM Profiler v1.1 has been released!

  - by FransBouma

  We've released ORM Profiler v1.1, which has the following new features: Real time profiling A real time viewer (RTV) has been added, which gives insight in the activity as it is received by the client, in two views: a chronological connection overview and an activity graph overview. This RTV allows the user to directly record to a snapshot using record buttons, pause the view, mark a range to create a snapshot from that range, and view graphs about the # of connection open actions and # of commands per second. The RTV has a 'range' in which it keeps live data and auto-cleans data that's older than this range. Screenshot of the activity graphs part of the real-time viewer: Low-level activity tab A new tab has been added to the Application tabs: the Low-level activity tab. This tab shows the main activity as it has been received over the named pipe. It can help to get insight in the chronological activity without the grouping over connections, so multiple connections at the same time per thread are easier to spot. Clicking a command will sync the rest of the application tabs, clicking a row will show the details below the splitter bar, as it is done with the other application tabs as well. Default application name in interceptor When an empty string or null is passed for application name to the Initialize method of the interceptor, the AppDomain's friendly name is used instead. Copy call stack to clipboard A call stack viewed in a grid in various parts of the UI is now copyable to the clipboard by clicking a button. Enable/Disable interceptor from the config file It's now possible to enable/disable the interceptor Initialization from the application's config file, using: Code: <appSettings> <add key="ORMProfilerEnabled" value="true"/> </appSettings> if value is true, the interceptor's Initialize method will proceed. If the value is false, the interceptor's Initialize method will not proceed and initialization won't be performed, meaning no interception will take place. If the setting is absent, or misconfigured, the Initialize method will proceed as normal and perform the initialization. Stored procedure calls for select databases are now properly displayed as a call For the databases: SQL Server, Oracle, DB2, Sybase ASA, Sybase ASE and Informix a stored procedure call is displayed as an execute/call statement and copy to clipboard works as-is. I'm especially happy with the new real-time profiling feature in ORM Profiler, which is the flagship feature for this release: it offers a completely new way to use the profiler, namely directly during debugging: you can immediately see what's going on without the necessity of a snapshot. The activity graph feature combined with the auto-cleanup of older data, allows you to keep the profiler open for a long period of time and see any spike of activity on the profiled application.

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• SQLAuthority News – Technical Review of Learning at Koenig Solutions

  - by pinaldave

  Yesterday I finished my 3 days fast track in person learning of course End to End SQL Server Business Intelligence at Koenig Solutions. You can read my previous article over here regarding why am I learning SQL Server. Yesterday I blogged about my experience of arriving to Training Center and my induction with the center. The Training Days I had enrolled for three days training so my routine each of the three days was very much same. However, the content every day was different as I was learning something new every day. Let me describe a few of the interesting details of my daily routine. A Single Student Batch The best part of my training was that in my training batch, I am single student. Koenig is known to smaller batches and often they have single student batches as well. I was very much delighted to know that I will have dedicated access and attention from my trainer in my batch as I will be single student in my batch. In most of the labs I have observed there are no more than 4 students at any time. Prakash and Pinal 7:30 AM Breakfast Talk We all students gather at 7:30 in breakfast area. The best time of the day. I was the only Indian student in the group. The other students were from USA, Canada, Nigeria, Bhutan, Tanzania, and a few others from other countries. I immediately become the source of information and reference manual. Though the distance between Delhi and Bangalore is 2000+ KM I was considered as a local guy. 8:30 AMHeading to Training Center Every day without fail at 8:30 the van started from our accommodation to the training center. As mentioned in an earlier blog post the distance is about 5 minutes and we were able to reach at the location before 8:45. This gave us some time settle in before our class starts at 9:00 AM. 9:00 AM Order Lunch Food Well it may sound funny that we just had breakfast 30 minutes but the first thing everybody has to do is to order lunch as soon as the class starts. There is an online training portal to order food for the day. Everybody has to place their order early during the day so the food arrives on time during lunch time. Everybody can order whatever they want to order using an online ordering system. The options are plenty and everybody can order what they like. 9:05 AM Learning Starts After deciding the lunch we started the learning. I was very fortunate to have a very experienced trainer - Prakash Chheatry. Though I have never met him before I have heard a lot about Prakash. He is known as the top most SQL Server Trainer in India. His student list contains some of the very well known SQL Server Experts of the world and few of SQL Server “best seller” book authors. Learning continues till 1:00 PM with one tea-coffee break in between. 1:00 PM Lunch The lunch time is again the fun time. We all students get together in the afternoon and tell the stories of the world. Indeed the best part of the day beside learning new stuff. 4:55 PM Ready to Return We stop at 4:55 as at precisely 5:00 PM the van stops by the institute which takes us back to our accommodation. Trust me seriously long long day always but the amount of the learning is the win of the day. 7:30 PM Dinner Time After coming back to the accommodation I study till 7:30 and then rush for dinner. Dinner is world cuisine and deserts are really delicious. After dinner every day I have written a blog and retired early as the next day is always going to be busier than the present day. What did I learn As I mentioned earlier I know SQL Server fairly well. I had expressed the same in my conversation as well. This is the reason I was assigned a fairly senior trainer and we learned everything quite quickly. As I know quite a few things we went pretty fast in many topics. There were a few things, I wanted to learn in detail as well practice on the labs. We slowed down where we wanted and rush through the concepts where I was very comfortable. Here is the list of the things which we covered in action pack three days. Introduction to Business Intelligence (Intro) SQL Server Analysis Service (Theory and Lab) SQL Server Integration Service  (Theory and Lab) SQL Server Reporting Service  (Theory and Lab) SQL Server PowerPivot (Lab) UDM (Theory) SharePoint Concepts (Theory) Power View (Demo) Business Intelligence and Security (Discussion) Well, I was delighted that I was able to refresh lots of concepts during these three days. Thanks to my trainer and my friend who helped me to have a good learning experience. I believe all the learning  will help me in my growth and future career. With this I end my this experience. I am planning to have another online learning experience later this month. I will blog about my experience as I begin it. Reference: Pinal Dave (http://blog.sqlauthority.com) Filed under: PostADay, SQL, SQL Authority, SQL Query, SQL Server, SQL Tips and Tricks, SQL Training, T SQL, Technology

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• What to do if you're burnt out?

  - by rsteckly

  Hi, I'm starting to get really frustrated with ASP.NET. It seems as if much of my time is spent learning abstractions over problems, then having to kick into overdrive when those abstractions (surprise!) have unexpected behavior. It seems as if I spend so much time just fixing those issues because they usually are UI related and therefore require integration testing that I spend very little time programming any kind of meaningful logic. I don't know if it is ASP or if it is programming. I just feel as if I'm getting paid, doing the work but really wasting time. On the other hand, I have fantasies about console programs and actually using algorithms. What is wrong with me? Why can't I force myself to churn through this ASP stuff more?

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