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• Data Source Security Part 4

  - by Steve Felts

  So far, I have covered Client Identity and Oracle Proxy Session features, with WLS or database credentials.  This article will cover one more feature, Identify-based pooling.  Then, there is one more topic to cover - how these options play with transactions.Identity-based Connection Pooling An identity based pool creates a heterogeneous pool of connections.  This allows applications to use a JDBC connection with a specific DBMS credential by pooling physical connections with different DBMS credentials.  The DBMS credential is based on either the WebLogic user mapped to a database user or the database user directly, based on the “use database credentials” setting as described earlier. Using this feature enabled with “use database credentials” enabled seems to be what is proposed in the JDBC standard, basically a heterogeneous pool with users specified by getConnection(user, password). The allocation of connections is more complex if Enable Identity Based Connection Pooling attribute is enabled on the data source.  When an application requests a database connection, the WebLogic Server instance selects an existing physical connection or creates a new physical connection with requested DBMS identity. The following section provides information on how heterogeneous connections are created:1. At connection pool initialization, the physical JDBC connections based on the configured or default “initial capacity” are created with the configured default DBMS credential of the data source.2. An application tries to get a connection from a data source.3a. If “use database credentials” is not enabled, the user specified in getConnection is mapped to a DBMS credential, as described earlier.  If the credential map doesn’t have a matching user, the default DBMS credential is used from the datasource descriptor.3b. If “use database credentials” is enabled, the user and password specified in getConnection are used directly.4. The connection pool is searched for a connection with a matching DBMS credential.5. If a match is found, the connection is reserved and returned to the application.6. If no match is found, a connection is created or reused based on the maximum capacity of the pool: - If the maximum capacity has not been reached, a new connection is created with the DBMS credential, reserved, and returned to the application.- If the pool has reached maximum capacity, based on the least recently used (LRU) algorithm, a physical connection is selected from the pool and destroyed. A new connection is created with the DBMS credential, reserved, and returned to the application. It should be clear that finding a matching connection is more expensive than a homogeneous pool.  Destroying a connection and getting a new one is very expensive.  If you can use a normal homogeneous pool or one of the light-weight options (client identity or an Oracle proxy connection), those should be used instead of identity based pooling. Regardless of how physical connections are created, each physical connection in the pool has its own DBMS credential information maintained by the pool. Once a physical connection is reserved by the pool, it does not change its DBMS credential even if the current thread changes its WebLogic user credential and continues to use the same connection. To configure this feature, select Enable Identity Based Connection Pooling.  See http://docs.oracle.com/cd/E24329_01/apirefs.1211/e24401/taskhelp/jdbc/jdbc_datasources/EnableIdentityBasedConnectionPooling.html  "Enable identity-based connection pooling for a JDBC data source" in Oracle WebLogic Server Administration Console Help. You must make the following changes to use Logging Last Resource (LLR) transaction optimization with Identity-based Pooling to get around the problem that multiple users will be accessing the associated transaction table.- You must configure a custom schema for LLR using a fully qualified LLR table name. All LLR connections will then use the named schema rather than the default schema when accessing the LLR transaction table.  - Use database specific administration tools to grant permission to access the named LLR table to all users that could access this table via a global transaction. By default, the LLR table is created during boot by the user configured for the connection in the data source. In most cases, the database will only allow access to this user and not allow access to mapped users. Connections within Transactions Now that we have covered the behavior of all of these various options, it’s time to discuss the exception to all of the rules.  When you get a connection within a transaction, it is associated with the transaction context on a particular WLS instance. When getting a connection with a data source configured with non-XA LLR or 1PC (using the JTS driver) with global transactions, the first connection obtained within the transaction is returned on subsequent connection requests regardless of the values of username/password specified and independent of the associated proxy user session, if any. The connection must be shared among all users of the connection when using LLR or 1PC. For XA data sources, the first connection obtained within the global transaction is returned on subsequent connection requests within the application server, regardless of the values of username/password specified and independent of the associated proxy user session, if any.  The connection must be shared among all users of the connection within a global transaction within the application server/JVM.

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• EMC's Really Big Storage Network

  EMC's Atmos cloud storage system gets new levels of data protection and a big boost in performance and capacity.

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• What is the best private cloud storage setup

  - by vdrmrt

  I need to create a private cloud and I'm searching for the best setup. These are my 2 most important requirements 1. Disk and system redundant 2. Price / GB as low as possible The system is going to be used as backup setup which will receive data 24/7 over SFTP and rsync. High throughput is not that important. I'm planning to use glusterfs and consumer grade 4TB hard-drives. I have worked out 3 possible setups 3 servers with 11 4TB HDD Setup up a replica 3 glusterfs and setup each hard drive as a separate ext4 brick. Total capacity: 44TB HDD / TB ratio of 0.75 (33HDD / 44TB) 2 servers with 11 4TB HDD The 11 hard-drives are combined in a RAIDZ3 ZFS storage pool. With a replica 2 gluster setup. Total capacity: 32TB (+ zfs compression) HDD / TB ratio of 0.68 (22HDD / 32TB) 3 servers with 11 4TB consumer hard-drives Setup up a replica 3 glusterfs and setup each hard-drive as a separate zfs storage pool and export each pool as a brick. Total capacity: 32TB (+ zfs compression) HDD / TB ratio of 0.68 (22HDD / 32TB) (Cheapest) My remarks and concerns: If a hard drive fails which setup will recover the quickest? In my opinion setup 1 and 3 because there only the contents of 1 hard-drive needs to be copied over the network. Instead of setup 2 were the hard-drive needs te be reconstructed by reading the parity of all the other harddrives in the system. Will a zfs pool on 1 harddrive give me extra protection against for example bit rot? With setup 1 and 3 I can loose 2 systems and still be up and running with setup 2 I can only loose 1 system. When I use ZFS I can enable compression which will give me some extra storage.

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• How to calibrate ASUS k52f battery on Ubuntu?

  - by cutalion

  I'm not sure if the problem is in software or my battery is dying, I'll move my question to another forum if it's not a SO question I have a problem with the battery on my laptop - ASUS K52F. It shows incorrect information about capacity. When I unplug the charger it can work some time, but then it will power off without any warnings. Sometimes it will power off right after I unplug the charger. Here is some info I could get: > uname -a Linux alligator 3.5.0-18-generic #29-Ubuntu SMP Fri Oct 19 10:26:51 UTC 2012 x86_64 x86_64 x86_64 GNU/Linux > acpi -i Battery 0: Charging, 99%, 18:25:15 until charged Battery 0: design capacity 5235 mAh, last full capacity 69964 mAh = 100% > cat /sys/class/power_supply/BAT0/uevent POWER_SUPPLY_NAME=BAT0 POWER_SUPPLY_STATUS=Charging POWER_SUPPLY_PRESENT=1 POWER_SUPPLY_TECHNOLOGY=Li-ion POWER_SUPPLY_CYCLE_COUNT=0 POWER_SUPPLY_VOLTAGE_MIN_DESIGN=10800000 POWER_SUPPLY_VOLTAGE_NOW=9246000 POWER_SUPPLY_POWER_NOW=176000 POWER_SUPPLY_ENERGY_FULL_DESIGN=**48400000** POWER_SUPPLY_ENERGY_FULL=**646822000** POWER_SUPPLY_ENERGY_NOW=**643588000** POWER_SUPPLY_MODEL_NAME=K52F-44 POWER_SUPPLY_MANUFACTURER=ASUSTek POWER_SUPPLY_SERIAL_NUMBER= I noticed, that POWER_SUPPLY_ENERGY_NOW and POWER_SUPPLY_ENERGY_FULL are greater than POWER_SUPPLY_ENERGY_FULL_DESIGN. I don't think it's ok :) I can run any additional commands.

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• external drive and CentOS - Reset high speed USB device number

  - by Phil

  I have 2 external drives (3TB) and both will not work with my centOS Box. Tested them in windows ( different machine ) No problems ( 2.6.32-279.9.1.el6.i686 ) dmesg reports: usb 2-2: new high speed USB device number 3 using ehci_hcd usb 2-2: New USB device found, idVendor=2109, idProduct=0700 usb 2-2: New USB device strings: Mfr=1, Product=2, SerialNumber=3 usb 2-2: Product: USB 3.0 SATA Bridge usb 2-2: Manufacturer: VIA Labs, Inc. usb 2-2: SerialNumber: 0000000000006121 usb 2-2: configuration #1 chosen from 1 choice scsi6 : SCSI emulation for USB Mass Storage devices usb-storage: device found at 3 usb-storage: waiting for device to settle before scanning usb-storage: device scan complete scsi 6:0:0:0: Direct-Access ST3000DM 001-9YN166 CC4B PQ: 0 ANSI: 2 sd 6:0:0:0: Attached scsi generic sg3 type 0 sd 6:0:0:0: [sdd] Very big device. Trying to use READ CAPACITY(16). sd 6:0:0:0: [sdd] 5860533165 512-byte logical blocks: (3.00 TB/2.72 TiB) sd 6:0:0:0: [sdd] Write Protect is off sd 6:0:0:0: [sdd] Mode Sense: 00 06 00 00 sd 6:0:0:0: [sdd] Assuming drive cache: write through sd 6:0:0:0: [sdd] Very big device. Trying to use READ CAPACITY(16). sd 6:0:0:0: [sdd] Assuming drive cache: write through sdd: sdd1 sd 6:0:0:0: [sdd] Very big device. Trying to use READ CAPACITY(16). sd 6:0:0:0: [sdd] Assuming drive cache: write through sd 6:0:0:0: [sdd] Attached SCSI disk Tyring to use cfdisk / fdisk / gdisk or even fdisk -l results in the program hanging and dmesg reports: usb 2-2: reset high speed USB device number 3 using ehci_hcd usb 2-2: reset high speed USB device number 3 using ehci_hcd usb 2-2: reset high speed USB device number 3 using ehci_hcd I have the same 2 drives physically installed in the computer via SATA Any Ideas?

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• How to boost playback volume in real time on media recorded with a very low volume.

  - by L Marksman

  I have never heard a satisfactory answer to this often misunderstood question, let me explain. Lets say I have a sound card and earphones/speakers that can play back audio loud enough in most cases. This is great but the problem is that you always find people who do not know how to record audio, from Youtube video's to music. So now you end up with a audio playback that only uses 10% or less of the capacity of your sound hardware, in vista/win 7 you will see this frequently in the mixer with the volume pushed up to max but the green sound level only goes up a millimeter or two. I am looking for (preferably free) software or a method to boost the sound level of any audio from any source in real time to use more of my hardware capacity similar to what VLC media player can do. Oh and please, do not tell me it is impossible. I am not trying to boost the volume past what my hardware is capable of, I am just trying to use my hardware's full capacity. Also please do not tell met to buy new hardware, I know I can use hardware amplification, I don't want to (like many others) spend money on a simple little problem like this. Thanks!

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• Why is shrink_to_fit non-binding?

  - by Roger Pate

  The C++0x FCD states in 23.3.6.2 vector capacity: void shrink_to_fit(); Remarks: shrink_to_fit is a non-binding request to reduce capacity() to size(). [Note: The request is non-binding to allow latitude for implementation-specific optimizations. —end note] Why is it non-binding, and what optimizations are intended to be allowed?

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• Convert NSData into Hex NSString

  - by Dawson

  With reference to the following question: Convert NSData into HEX NSSString I have solved the problem using the solution provided by Erik Aigner which is: NSData *data = ...; NSUInteger capacity = [data length] * 2; NSMutableString *stringBuffer = [NSMutableString stringWithCapacity:capacity]; const unsigned char *dataBuffer = [data bytes]; NSInteger i; for (i=0; i<[data length]; ++i) { [stringBuffer appendFormat:@"%02X", (NSUInteger)dataBuffer[i]]; } However, there is one small problem in that if there are extra zeros at the back, the string value would be different. For eg. if the hexa data is of a string @"3700000000000000", when converted using a scanner to integer: unsigned result = 0; NSScanner *scanner = [NSScanner scannerWithString:stringBuffer]; [scanner scanHexInt:&result]; NSLog(@"INTEGER: %u",result); The result would be 4294967295, which is incorrect. Shouldn't it be 55 as only the hexa 37 is taken? So how do I get rid of the zeros? EDIT: (In response to CRD) Hi, thanks for clarifying my doubts. So what you're doing is to actually read the 64-bit integer directly from a byte pointer right? However I have another question. How do you actually cast NSData to a byte pointer? To make it easier for you to understand, I'll explain what I did originally. Firstly, what I did was to display the data of the file which I have (data is in hexadecimal) NSData *file = [NSData dataWithContentsOfFile:@"file path here"]; NSLog(@"Patch File: %@",file); Output: Next, what I did was to read and offset the first 8 bytes of the file and convert them into a string. // 0-8 bytes [file seekToFileOffset:0]; NSData *b = [file readDataOfLength:8]; NSUInteger capacity = [b length] * 2; NSMutableString *stringBuffer = [NSMutableString stringWithCapacity:capacity]; const unsigned char *dataBuffer = [b bytes]; NSInteger i; for (i=0; i<[b length]; ++i) { [stringBuffer appendFormat:@"%02X", (NSUInteger)dataBuffer[i]]; } NSLog(@"0-8 bytes HEXADECIMAL: %@",stringBuffer); As you can see, 0x3700000000000000 is the next 8 bytes. The only changes I would have to make to access the next 8 bytes would be to change the value of SeekFileToOffset to 8, so as to access the next 8 bytes of data. All in all, the solution you gave me is useful, however it would not be practical to enter the hexadecimal values manually. If formatting the bytes as a string and then parsing them is not the way to do it, then how do I access the first 8 bytes of the data directly and cast them into a byte pointer?

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• using dictionaries with WebServices

  - by umit-alba

  Hi! I tried to pass a dictionary via WebServices. However it is not serializeable. So i wrote an Own Class that makes it serializeable: using System; using System.Net; using System.Windows; using System.Collections.Generic; using System.Xml.Serialization; using System.Xml; using System.Xml.Schema; namespace Platform { public class SaDictionary<TKey, TValue> : Dictionary<TKey, TValue>, IXmlSerializable { #region Constructors public SaDictionary() : base() { } public SaDictionary(IDictionary<TKey, TValue> dictionary) : base(dictionary) { } public SaDictionary(IEqualityComparer<TKey> comparer) : base(comparer) { } public SaDictionary(int capacity) : base(capacity) { } public SaDictionary(IDictionary<TKey, TValue> dictionary, IEqualityComparer<TKey> comparer) : base(dictionary, comparer) { } public SaDictionary(int capacity, IEqualityComparer<TKey> comparer) : base(capacity, comparer) { } //protected SaDictionary(SerializationInfo info, StreamingContext context) // : base(info, context) //{ //} #endregion public XmlSchema GetSchema() { return null; } public void ReadXml(XmlReader reader) { XmlSerializer keySerializer = new XmlSerializer(typeof(TKey)); XmlSerializer valueSerializer = new XmlSerializer(typeof(TValue)); bool wasEmpty = reader.IsEmptyElement; reader.Read(); if (wasEmpty) return; while (reader.NodeType != XmlNodeType.EndElement) { reader.ReadStartElement("item"); reader.ReadStartElement("key"); TKey key = (TKey)keySerializer.Deserialize(reader); reader.ReadEndElement(); //key reader.ReadStartElement("value"); TValue value = (TValue)valueSerializer.Deserialize(reader); reader.ReadEndElement(); //value this.Add(key, value); reader.ReadEndElement(); //item // reader.MoveToContent(); } reader.ReadEndElement(); } public void WriteXml(XmlWriter writer) { XmlSerializer keySerializer = new XmlSerializer(typeof(TKey)); XmlSerializer valueSerializer = new XmlSerializer(typeof(TValue)); foreach (TKey key in this.Keys) { writer.WriteStartElement("item"); writer.WriteStartElement("key"); keySerializer.Serialize(writer, key); writer.WriteEndElement(); //key writer.WriteStartElement("value"); TValue value = this[key]; valueSerializer.Serialize(writer, value); writer.WriteEndElement(); //value writer.WriteEndElement(); //item } } } } However i get an ArrayOfXElement back. Is there a way to cast it back to a Dictionary? greets

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• inline and member initializers

  - by Alexander

  When should I inline a member function and when should I use member initializers? My code is below.. I would like to modify it so I could make use some inline when appropriate and member initializers: #include "Books.h" Book::Book(){ nm = (char*)""; thck = 0; wght = 0; } Book::Book(const char *name, int thickness, int weight){ nm = strdup(name); thck = thickness; wght = weight; } Book::~Book(){ } const char* Book::name(){ return nm; } int Book::thickness(){ return thck; } int Book::weight(){ return wght; } // // Prints information about the book using this format: // "%s (%d mm, %d dg)\n" // void Book::print(){ printf("%s (%d mm, %d dg)\n", nm, thck, wght); } Bookcase::Bookcase(int id){ my_id = id; no_shelf = 0; } int Bookcase::id(){ return my_id; } Bookcase::~Bookcase(){ for (int i = 0; i < no_shelf; i++) delete my_shelf[i]; } bool Bookcase::addShelf(int width, int capacity){ if(no_shelf == 10) return false; else{ my_shelf[no_shelf] = new Shelf(width, capacity); no_shelf++; return true; } } bool Bookcase::add(Book *bp){ int index = -1; int temp_space = -1; for (int i = 0; i < no_shelf; i++){ if (bp->weight() + my_shelf[i]->curCapacity() <= my_shelf[i]->capacity()){ if (bp->thickness() + my_shelf[i]->curWidth() <= my_shelf[i]->width() && temp_space < (my_shelf[i]->width() - my_shelf[i]->curWidth())){ temp_space = (my_shelf[i]->width()- my_shelf[i]->curWidth()); index = i; } } } if (index != -1){ my_shelf[index]->add(bp); return true; }else return false; } void Bookcase::print(){ printf("Bookcase #%d\n", my_id); for (int i = 0; i < no_shelf; i++){ printf("--- Shelf (%d mm, %d dg) ---\n", my_shelf[i]->width(), my_shelf[i]->capacity()); my_shelf[i]->print(); } }

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• Calling a Add-in function from Excel's VBA

  - by graham

  I am using an Excel Add-in for an Erlangs: http://abstractmicro.com/erlang/helppages/ref-erlbblockage.htm I try to call the Erlang-B function within the Add-in from within VBA thus: Function Erl(Erlangs As Double, Capacity As Double) Erl = Application.WorksheetFunction.ErlbBlockage(Capacity, Erlangs) End Function ...but it doesn't work. I get #VALUE! returned in the Excel cell. I think it is because the function is not part of standard Excel (it is in the Add-in). So how do I call it?

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• The Benefits of Smart Grid Business Software

  - by Sylvie MacKenzie, PMP

  Smart Grid Background What Are Smart Grids?Smart Grids use computer hardware and software, sensors, controls, and telecommunications equipment and services to: Link customers to information that helps them manage consumption and use electricity wisely. Enable customers to respond to utility notices in ways that help minimize the duration of overloads, bottlenecks, and outages. Provide utilities with information that helps them improve performance and control costs. What Is Driving Smart Grid Development? Environmental ImpactSmart Grid development is picking up speed because of the widespread interest in reducing the negative impact that energy use has on the environment. Smart Grids use technology to drive efficiencies in transmission, distribution, and consumption. As a result, utilities can serve customers’ power needs with fewer generating plants, fewer transmission and distribution assets,and lower overall generation. With the possible exception of wind farm sprawl, landscape preservation is one obvious benefit. And because most generation today results in greenhouse gas emissions, Smart Grids reduce air pollution and the potential for global climate change.Smart Grids also more easily accommodate the technical difficulties of integrating intermittent renewable resources like wind and solar into the grid, providing further greenhouse gas reductions. CostsThe ability to defer the cost of plant and grid expansion is a major benefit to both utilities and customers. Utilities do not need to use as many internal resources for traditional infrastructure project planning and management. Large T&D infrastructure expansion costs are not passed on to customers.Smart Grids will not eliminate capital expansion, of course. Transmission corridors to connect renewable generation with customers will require major near-term expenditures. Additionally, in the future, electricity to satisfy the needs of population growth and additional applications will exceed the capacity reductions available through the Smart Grid. At that point, expansion will resume—but with greater overall T&D efficiency based on demand response, load control, and many other Smart Grid technologies and business processes. Energy efficiency is a second area of Smart Grid cost saving of particular relevance to customers. The timely and detailed information Smart Grids provide encourages customers to limit waste, adopt energy-efficient building codes and standards, and invest in energy efficient appliances. Efficiency may or may not lower customer bills because customer efficiency savings may be offset by higher costs in generation fuels or carbon taxes. It is clear, however, that bills will be lower with efficiency than without it. Utility Operations Smart Grids can serve as the central focus of utility initiatives to improve business processes. Many utilities have long “wish lists” of projects and applications they would like to fund in order to improve customer service or ease staff’s burden of repetitious work, but they have difficulty cost-justifying the changes, especially in the short term. Adding Smart Grid benefits to the cost/benefit analysis frequently tips the scales in favor of the change and can also significantly reduce payback periods.Mobile workforce applications and asset management applications work together to deploy assets and then to maintain, repair, and replace them. Many additional benefits result—for instance, increased productivity and fuel savings from better routing. Similarly, customer portals that provide customers with near-real-time information can also encourage online payments, thus lowering billing costs. Utilities can and should include these cost and service improvements in the list of Smart Grid benefits. What Is Smart Grid Business Software? Smart Grid business software gathers data from a Smart Grid and uses it improve a utility’s business processes. Smart Grid business software also helps utilities provide relevant information to customers who can then use it to reduce their own consumption and improve their environmental profiles. Smart Grid Business Software Minimizes the Impact of Peak Demand Utilities must size their assets to accommodate their highest peak demand. The higher the peak rises above base demand: The more assets a utility must build that are used only for brief periods—an inefficient use of capital. The higher the utility’s risk profile rises given the uncertainties surrounding the time needed for permitting, building, and recouping costs. The higher the costs for utilities to purchase supply, because generators can charge more for contracts and spot supply during high-demand periods. Smart Grids enable a variety of programs that reduce peak demand, including: Time-of-use pricing and critical peak pricing—programs that charge customers more when they consume electricity during peak periods. Pilot projects indicate that these programs are successful in flattening peaks, thus ensuring better use of existing T&D and generation assets. Direct load control, which lets utilities reduce or eliminate electricity flow to customer equipment (such as air conditioners). Contracts govern the terms and conditions of these turn-offs. Indirect load control, which signals customers to reduce the use of on-premises equipment for contractually agreed-on time periods. Smart Grid business software enables utilities to impose penalties on customers who do not comply with their contracts. Smart Grids also help utilities manage peaks with existing assets by enabling: Real-time asset monitoring and control. In this application, advanced sensors safely enable dynamic capacity load limits, ensuring that all grid assets can be used to their maximum capacity during peak demand periods. Real-time asset monitoring and control applications also detect the location of excessive losses and pinpoint need for mitigation and asset replacements. As a result, utilities reduce outage risk and guard against excess capacity or “over-build”. Better peak demand analysis. As a result: Distribution planners can better size equipment (e.g. transformers) to avoid over-building. Operations engineers can identify and resolve bottlenecks and other inefficiencies that may cause or exacerbate peaks. As above, the result is a reduction in the tendency to over-build. Supply managers can more closely match procurement with delivery. As a result, they can fine-tune supply portfolios, reducing the tendency to over-contract for peak supply and reducing the need to resort to spot market purchases during high peaks. Smart Grids can help lower the cost of remaining peaks by: Standardizing interconnections for new distributed resources (such as electricity storage devices). Placing the interconnections where needed to support anticipated grid congestion. Smart Grid Business Software Lowers the Cost of Field Services By processing Smart Grid data through their business software, utilities can reduce such field costs as: Vegetation management. Smart Grids can pinpoint momentary interruptions and tree-caused outages. Spatial mash-up tools leverage GIS models of tree growth for targeted vegetation management. This reduces the cost of unnecessary tree trimming. Service vehicle fuel. Many utility service calls are “false alarms.” Checking meter status before dispatching crews prevents many unnecessary “truck rolls.” Similarly, crews use far less fuel when Smart Grid sensors can pinpoint a problem and mobile workforce applications can then route them directly to it. Smart Grid Business Software Ensures Regulatory Compliance Smart Grids can ensure compliance with private contracts and with regional, national, or international requirements by: Monitoring fulfillment of contract terms. Utilities can use one-hour interval meters to ensure that interruptible (“non-core”) customers actually reduce or eliminate deliveries as required. They can use the information to levy fines against contract violators. Monitoring regulations imposed on customers, such as maximum use during specific time periods. Using accurate time-stamped event history derived from intelligent devices distributed throughout the smart grid to monitor and report reliability statistics and risk compliance. Automating business processes and activities that ensure compliance with security and reliability measures (e.g. NERC-CIP 2-9). Grid Business Software Strengthens Utilities’ Connection to Customers While Reducing Customer Service Costs During outages, Smart Grid business software can: Identify outages more quickly. Software uses sensors to pinpoint outages and nested outage locations. They also permit utilities to ensure outage resolution at every meter location. Size outages more accurately, permitting utilities to dispatch crews that have the skills needed, in appropriate numbers. Provide updates on outage location and expected duration. This information helps call centers inform customers about the timing of service restoration. Smart Grids also facilitates display of outage maps for customer and public-service use. Smart Grids can significantly reduce the cost to: Connect and disconnect customers. Meters capable of remote disconnect can virtually eliminate the costs of field crews and vehicles previously required to change service from the old to the new residents of a metered property or disconnect customers for nonpayment. Resolve reports of voltage fluctuation. Smart Grids gather and report voltage and power quality data from meters and grid sensors, enabling utilities to pinpoint reported problems or resolve them before customers complain. Detect and resolve non-technical losses (e.g. theft). Smart Grids can identify illegal attempts to reconnect meters or to use electricity in supposedly vacant premises. They can also detect theft by comparing flows through delivery assets with billed consumption. Smart Grids also facilitate outreach to customers. By monitoring and analyzing consumption over time, utilities can: Identify customers with unusually high usage and contact them before they receive a bill. They can also suggest conservation techniques that might help to limit consumption. This can head off “high bill” complaints to the contact center. Note that such “high usage” or “additional charges apply because you are out of range” notices—frequently via text messaging—are already common among mobile phone providers. Help customers identify appropriate bill payment alternatives (budget billing, prepayment, etc.). Help customers find and reduce causes of over-consumption. There’s no waiting for bills in the mail before they even understand there is a problem. Utilities benefit not just through improved customer relations but also through limiting the size of bills from customers who might struggle to pay them. Where permitted, Smart Grids can open the doors to such new utility service offerings as: Monitoring properties. Landlords reduce costs of vacant properties when utilities notify them of unexpected energy or water consumption. Utilities can perform similar services for owners of vacation properties or the adult children of aging parents. Monitoring equipment. Power-use patterns can reveal a need for equipment maintenance. Smart Grids permit utilities to alert owners or managers to a need for maintenance or replacement. Facilitating home and small-business networks. Smart Grids can provide a gateway to equipment networks that automate control or let owners access equipment remotely. They also facilitate net metering, offering some utilities a path toward involvement in small-scale solar or wind generation. Prepayment plans that do not need special meters. Smart Grid Business Software Helps Customers Control Energy Costs There is no end to the ways Smart Grids help both small and large customers control energy costs. For instance: Multi-premises customers appreciate having all meters read on the same day so that they can more easily compare consumption at various sites. Customers in competitive regions can match their consumption profile (detailed via Smart Grid data) with specific offerings from competitive suppliers. Customers seeing inexplicable consumption patterns and power quality problems may investigate further. The result can be discovery of electrical problems that can be resolved through rewiring or maintenance—before more serious fires or accidents happen. Smart Grid Business Software Facilitates Use of Renewables Generation from wind and solar resources is a popular alternative to fossil fuel generation, which emits greenhouse gases. Wind and solar generation may also increase energy security in regions that currently import fossil fuel for use in generation. Utilities face many technical issues as they attempt to integrate intermittent resource generation into traditional grids, which traditionally handle only fully dispatchable generation. Smart Grid business software helps solves many of these issues by: Detecting sudden drops in production from renewables-generated electricity (wind and solar) and automatically triggering electricity storage and smart appliance response to compensate as needed. Supporting industry-standard distributed generation interconnection processes to reduce interconnection costs and avoid adding renewable supplies to locations already subject to grid congestion. Facilitating modeling and monitoring of locally generated supply from renewables and thus helping to maximize their use. Increasing the efficiency of “net metering” (through which utilities can use electricity generated by customers) by: Providing data for analysis. Integrating the production and consumption aspects of customer accounts. During non-peak periods, such techniques enable utilities to increase the percent of renewable generation in their supply mix. During peak periods, Smart Grid business software controls circuit reconfiguration to maximize available capacity. Conclusion Utility missions are changing. Yesterday, they focused on delivery of reasonably priced energy and water. Tomorrow, their missions will expand to encompass sustainable use and environmental improvement.Smart Grids are key to helping utilities achieve this expanded mission. But they come at a relatively high price. Utilities will need to invest heavily in new hardware, software, business process development, and staff training. Customer investments in home area networks and smart appliances will be large. Learning to change the energy and water consumption habits of a lifetime could ultimately prove even more formidable tasks.Smart Grid business software can ease the cost and difficulties inherent in a needed transition to a more flexible, reliable, responsive electricity grid. Justifying its implementation, however, requires a full understanding of the benefits it brings—benefits that can ultimately help customers, utilities, communities, and the world address global issues like energy security and climate change while minimizing costs and maximizing customer convenience. This white paper is available for download here. For further information about Oracle's Primavera Solutions for Utilities, please read our Utilities e-book.

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• Extending Oracle CEP with Predictive Analytics

  - by vikram.shukla(at)oracle.com

  Introduction: OCEP is often used as a business rules engine to execute a set of business logic rules via CQL statements, and take decisions based on the outcome of those rules. There are times where configuring rules manually is sufficient because an application needs to deal with only a small and well-defined set of static rules. However, in many situations customers don't want to pre-define such rules for two reasons. First, they are dealing with events with lots of columns and manually crafting such rules for each column or a set of columns and combinations thereof is almost impossible. Second, they are content with probabilistic outcomes and do not care about 100% precision. The former is the case when a user is dealing with data with high dimensionality, the latter when an application can live with "false" positives as they can be discarded after further inspection, say by a Human Task component in a Business Process Management software. The primary goal of this blog post is to show how this can be achieved by combining OCEP with Oracle Data Mining® and leveraging the latter's rich set of algorithms and functionality to do predictive analytics in real time on streaming events. The secondary goal of this post is also to show how OCEP can be extended to invoke any arbitrary external computation in an RDBMS from within CEP. The extensible facility is known as the JDBC cartridge. The rest of the post describes the steps required to achieve this: We use the dataset available at http://blogs.oracle.com/datamining/2010/01/fraud_and_anomaly_detection_made_simple.html to showcase the capabilities. We use it to show how transaction anomalies or fraud can be detected. Building the model: Follow the self-explanatory steps described at the above URL to build the model.  It is very simple - it uses built-in Oracle Data Mining PL/SQL packages to cleanse, normalize and build the model out of the dataset.  You can also use graphical Oracle Data Miner®  to build the models. To summarize, it involves: Specifying which algorithms to use. In this case we use Support Vector Machines as we're trying to find anomalies in highly dimensional dataset.Build model on the data in the table for the algorithms specified. For this example, the table was populated in the scott/tiger schema with appropriate privileges. Configuring the Data Source: This is the first step in building CEP application using such an integration.  Our datasource looks as follows in the server config file.  It is advisable that you use the Visualizer to add it to the running server dynamically, rather than manually edit the file.    <data-source>         <name>DataMining</name>         <data-source-params>             <jndi-names>                 <element>DataMining</element>             </jndi-names>             <global-transactions-protocol>OnePhaseCommit</global-transactions-protocol>         </data-source-params>         <connection-pool-params>             <credential-mapping-enabled></credential-mapping-enabled>             <test-table-name>SQL SELECT 1 from DUAL</test-table-name>             <initial-capacity>1</initial-capacity>             <max-capacity>15</max-capacity>             <capacity-increment>1</capacity-increment>         </connection-pool-params>         <driver-params>             <use-xa-data-source-interface>true</use-xa-data-source-interface>             <driver-name>oracle.jdbc.OracleDriver</driver-name>             <url>jdbc:oracle:thin:@localhost:1522:orcl</url>             <properties>                 <element>                     <value>scott</value>                     <name>user</name>                 </element>                 <element>                     <value>{Salted-3DES}AzFE5dDbO2g=</value>                     <name>password</name>                 </element>                                 <element>                     <name>com.bea.core.datasource.serviceName</name>                     <value>oracle11.2g</value>                 </element>                 <element>                     <name>com.bea.core.datasource.serviceVersion</name>                     <value>11.2.0</value>                 </element>                 <element>                     <name>com.bea.core.datasource.serviceObjectClass</name>                     <value>java.sql.Driver</value>                 </element>             </properties>         </driver-params>     </data-source>   Designing the EPN: The EPN is very simple in this example. We briefly describe each of the components. The adapter ("DataMiningAdapter") reads data from a .csv file and sends it to the CQL processor downstream. The event payload here is same as that of the table in the database (refer to the attached project or do a "desc table-name" from a SQL*PLUS prompt). While this is for convenience in this example, it need not be the case. One can still omit fields in the streaming events, and need not match all columns in the table on which the model was built. Better yet, it does not even need to have the same name as columns in the table, as long as you alias them in the USING clause of the mining function. (Caveat: they still need to draw values from a similar universe or domain, otherwise it constitutes incorrect usage of the model). There are two things in the CQL processor ("DataMiningProc") that make scoring possible on streaming events. 1.      User defined cartridge function Please refer to the OCEP CQL reference manual to find more details about how to define such functions. We include the function below in its entirety for illustration. <?xml version="1.0" encoding="UTF-8"?> <jdbcctxconfig:config     xmlns:jdbcctxconfig="http://www.bea.com/ns/wlevs/config/application"     xmlns:jc="http://www.oracle.com/ns/ocep/config/jdbc">        <jc:jdbc-ctx>         <name>Oracle11gR2</name>         <data-source>DataMining</data-source>               <function name="prediction2">                                 <param name="CQLMONTH" type="char"/>                      <param name="WEEKOFMONTH" type="int"/>                      <param name="DAYOFWEEK" type="char" />                      <param name="MAKE" type="char" />                      <param name="ACCIDENTAREA"   type="char" />                      <param name="DAYOFWEEKCLAIMED"  type="char" />                      <param name="MONTHCLAIMED" type="char" />                      <param name="WEEKOFMONTHCLAIMED" type="int" />                      <param name="SEX" type="char" />                      <param name="MARITALSTATUS"   type="char" />                      <param name="AGE" type="int" />                      <param name="FAULT" type="char" />                      <param name="POLICYTYPE"   type="char" />                      <param name="VEHICLECATEGORY"  type="char" />                      <param name="VEHICLEPRICE" type="char" />                      <param name="FRAUDFOUND" type="int" />                      <param name="POLICYNUMBER" type="int" />                      <param name="REPNUMBER" type="int" />                      <param name="DEDUCTIBLE"   type="int" />                      <param name="DRIVERRATING"  type="int" />                      <param name="DAYSPOLICYACCIDENT"   type="char" />                      <param name="DAYSPOLICYCLAIM" type="char" />                      <param name="PASTNUMOFCLAIMS" type="char" />                      <param name="AGEOFVEHICLES" type="char" />                      <param name="AGEOFPOLICYHOLDER" type="char" />                      <param name="POLICEREPORTFILED" type="char" />                      <param name="WITNESSPRESNT" type="char" />                      <param name="AGENTTYPE" type="char" />                      <param name="NUMOFSUPP" type="char" />                      <param name="ADDRCHGCLAIM"   type="char" />                      <param name="NUMOFCARS" type="char" />                      <param name="CQLYEAR" type="int" />                      <param name="BASEPOLICY" type="char" />                                     <return-component-type>char</return-component-type>                                                      <sql><![CDATA[             SELECT to_char(PREDICTION_PROBABILITY(CLAIMSMODEL, '0' USING *))               AS probability             FROM (SELECT  :CQLMONTH AS MONTH,                                            :WEEKOFMONTH AS WEEKOFMONTH,                          :DAYOFWEEK AS DAYOFWEEK,                           :MAKE AS MAKE,                           :ACCIDENTAREA AS ACCIDENTAREA,                           :DAYOFWEEKCLAIMED AS DAYOFWEEKCLAIMED,                           :MONTHCLAIMED AS MONTHCLAIMED,                           :WEEKOFMONTHCLAIMED,                             :SEX AS SEX,                           :MARITALSTATUS AS MARITALSTATUS,                            :AGE AS AGE,                           :FAULT AS FAULT,                           :POLICYTYPE AS POLICYTYPE,                            :VEHICLECATEGORY AS VEHICLECATEGORY,                           :VEHICLEPRICE AS VEHICLEPRICE,                           :FRAUDFOUND AS FRAUDFOUND,                           :POLICYNUMBER AS POLICYNUMBER,                           :REPNUMBER AS REPNUMBER,                           :DEDUCTIBLE AS DEDUCTIBLE,                            :DRIVERRATING AS DRIVERRATING,                           :DAYSPOLICYACCIDENT AS DAYSPOLICYACCIDENT,                            :DAYSPOLICYCLAIM AS DAYSPOLICYCLAIM,                           :PASTNUMOFCLAIMS AS PASTNUMOFCLAIMS,                           :AGEOFVEHICLES AS AGEOFVEHICLES,                           :AGEOFPOLICYHOLDER AS AGEOFPOLICYHOLDER,                           :POLICEREPORTFILED AS POLICEREPORTFILED,                           :WITNESSPRESNT AS WITNESSPRESENT,                           :AGENTTYPE AS AGENTTYPE,                           :NUMOFSUPP AS NUMOFSUPP,                           :ADDRCHGCLAIM AS ADDRCHGCLAIM,                            :NUMOFCARS AS NUMOFCARS,                           :CQLYEAR AS YEAR,                           :BASEPOLICY AS BASEPOLICY                 FROM dual)                 ]]>         </sql>        </function>     </jc:jdbc-ctx> </jdbcctxconfig:config> 2.      Invoking the function for each event. Once this function is defined, you can invoke it from CQL as follows: <?xml version="1.0" encoding="UTF-8"?> <wlevs:config xmlns:wlevs="http://www.bea.com/ns/wlevs/config/application">   <processor>     <name>DataMiningProc</name>     <rules>        <query id="q1"><![CDATA[                     ISTREAM(SELECT S.CQLMONTH,                                   S.WEEKOFMONTH,                                   S.DAYOFWEEK, S.MAKE,                                   :                                         S.BASEPOLICY,                                    C.F AS probability                                                 FROM                                 StreamDataChannel [NOW] AS S,                                 TABLE(prediction2@Oracle11gR2(S.CQLMONTH,                                      S.WEEKOFMONTH,                                      S.DAYOFWEEK,                                       S.MAKE, ...,                                      S.BASEPOLICY) AS F of char) AS C)                       ]]></query>                 </rules>               </processor>           </wlevs:config>   Finally, the last stage in the EPN prints out the probability of the event being an anomaly. One can also define a threshold in CQL to filter out events that are normal, i.e., below a certain mark as defined by the analyst or designer. Sample Runs: Now let's see how this behaves when events are streamed through CEP. We use only two events for brevity, one normal and other one not. This is one of the "normal" looking events and the probability of it being anomalous is less than 60%. Event is: eventType=DataMiningOutEvent object=q1  time=2904821976256 S.CQLMONTH=Dec, S.WEEKOFMONTH=5, S.DAYOFWEEK=Wednesday, S.MAKE=Honda, S.ACCIDENTAREA=Urban, S.DAYOFWEEKCLAIMED=Tuesday, S.MONTHCLAIMED=Jan, S.WEEKOFMONTHCLAIMED=1, S.SEX=Female, S.MARITALSTATUS=Single, S.AGE=21, S.FAULT=Policy Holder, S.POLICYTYPE=Sport - Liability, S.VEHICLECATEGORY=Sport, S.VEHICLEPRICE=more than 69000, S.FRAUDFOUND=0, S.POLICYNUMBER=1, S.REPNUMBER=12, S.DEDUCTIBLE=300, S.DRIVERRATING=1, S.DAYSPOLICYACCIDENT=more than 30, S.DAYSPOLICYCLAIM=more than 30, S.PASTNUMOFCLAIMS=none, S.AGEOFVEHICLES=3 years, S.AGEOFPOLICYHOLDER=26 to 30, S.POLICEREPORTFILED=No, S.WITNESSPRESENT=No, S.AGENTTYPE=External, S.NUMOFSUPP=none, S.ADDRCHGCLAIM=1 year, S.NUMOFCARS=3 to 4, S.CQLYEAR=1994, S.BASEPOLICY=Liability, probability=.58931702982118561 isTotalOrderGuarantee=true\nAnamoly probability: .58931702982118561 However, the following event is scored as an anomaly with a very high probability of  89%. So there is likely to be something wrong with it. A close look reveals that the value of "deductible" field (10000) is not "normal". What exactly constitutes normal here?. If you run the query on the database to find ALL distinct values for the "deductible" field, it returns the following set: {300, 400, 500, 700} Event is: eventType=DataMiningOutEvent object=q1  time=2598483773496 S.CQLMONTH=Dec, S.WEEKOFMONTH=5, S.DAYOFWEEK=Wednesday, S.MAKE=Honda, S.ACCIDENTAREA=Urban, S.DAYOFWEEKCLAIMED=Tuesday, S.MONTHCLAIMED=Jan, S.WEEKOFMONTHCLAIMED=1, S.SEX=Female, S.MARITALSTATUS=Single, S.AGE=21, S.FAULT=Policy Holder, S.POLICYTYPE=Sport - Liability, S.VEHICLECATEGORY=Sport, S.VEHICLEPRICE=more than 69000, S.FRAUDFOUND=0, S.POLICYNUMBER=1, S.REPNUMBER=12, S.DEDUCTIBLE=10000, S.DRIVERRATING=1, S.DAYSPOLICYACCIDENT=more than 30, S.DAYSPOLICYCLAIM=more than 30, S.PASTNUMOFCLAIMS=none, S.AGEOFVEHICLES=3 years, S.AGEOFPOLICYHOLDER=26 to 30, S.POLICEREPORTFILED=No, S.WITNESSPRESENT=No, S.AGENTTYPE=External, S.NUMOFSUPP=none, S.ADDRCHGCLAIM=1 year, S.NUMOFCARS=3 to 4, S.CQLYEAR=1994, S.BASEPOLICY=Liability, probability=.89171554529576691 isTotalOrderGuarantee=true\nAnamoly probability: .89171554529576691 Conclusion: By way of this example, we show: real-time scoring of events as they flow through CEP leveraging Oracle Data Mining.how CEP applications can invoke complex arbitrary external computations (function shipping) in an RDBMS.

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• IPgallery banks on Solaris SPARC

  - by Frederic Pariente

  IPgallery is a global supplier of converged legacy and Next Generation Networks (NGN) products and solutions, including: core network components and cloud-based Value Added Services (VAS) for voice, video and data sessions. IPgallery enables network operators and service providers to offer advanced converged voice, chat, video/content services and rich unified social communications in a combined legacy (fixed/mobile), Over-the-Top (OTT) and Social Community (SC) environments for home and business customers. Technically speaking, this offer is a scalable and robust telco solution enabling operators to offer new services while controlling operating expenses (OPEX). In its solutions, IPgallery leverages the following Oracle components: Oracle Solaris, Netra T4 and SPARC T4 in order to provide a competitive and scalable solution without the price tag often associated with high-end systems. Oracle Solaris Binary Application Guarantee A unique feature of Oracle Solaris is the guaranteed binary compatibility between releases of the Solaris OS. That means, if a binary application runs on Solaris 2.6 or later, it will run on the latest release of Oracle Solaris.  IPgallery developed their application on Solaris 9 and Solaris 10 then runs it on Solaris 11, without any code modification or rebuild. The Solaris Binary Application Guarantee helps IPgallery protect their long-term investment in the development, training and maintenance of their applications. Oracle Solaris Image Packaging System (IPS) IPS is a new repository-based package management system that comes with Oracle Solaris 11. It provides a framework for complete software life-cycle management such as installation, upgrade and removal of software packages. IPgallery leverages this new packaging system in order to speed up and simplify software installation for the R&D and production environments. Notably, they use IPS to deliver Solaris Studio 12.3 packages as part of the rapid installation process of R&D environments, and during the production software deployment phase, they ensure software package integrity using the built-in verification feature. Solaris IPS thus improves IPgallery's time-to-market with a faster, more reliable software installation and deployment in production environments. Extreme Network Performance IPgallery saw a huge improvement in application performance both in CPU and I/O, when running on SPARC T4 architecture in compared to UltraSPARC T2 servers.  The same application (with the same activation environment) running on T2 consumes 40%-50% CPU, while it consumes only 10% of the CPU on T4. The testing environment comprised of: Softswitch (Call management), TappS (Telecom Application Server) and Billing Server running on same machine and initiating various services in capacity of 1000 CAPS (Call Attempts Per Second). In addition, tests showed a huge improvement in the performance of the TCP/IP stack, which reduces network layer processing and in the end Call Attempts latency. Finally, there is a huge improvement within the file system and disk I/O operations; they ran all tests with maximum logging capability and it didn't influence any benchmark values. "Due to the huge improvements in performance and capacity using the T4-1 architecture, IPgallery has engineered the solution with less hardware.  This means instead of deploying the solution on six T2-based machines, we will deploy on 2 redundant machines while utilizing Oracle Solaris Zones and Oracle VM for higher availability and virtualization" Shimon Lichter, VP R&D, IPgallery In conclusion, using the unique combination of Oracle Solaris and SPARC technologies, IPgallery is able to offer solutions with much lower TCO, while providing a higher level of service capacity, scalability and resiliency. This low-OPEX solution enables the operator, the end-customer, to deliver a high quality service while maintaining high profitability.

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• Instantiating class with custom allocator in shared memory

  - by recipriversexclusion

  I'm pulling my hair due to the following problem: I am following the example given in boost.interprocess documentation to instantiate a fixed-size ring buffer buffer class that I wrote in shared memory. The skeleton constructor for my class is: template<typename ItemType, class Allocator > SharedMemoryBuffer<ItemType, Allocator>::SharedMemoryBuffer( unsigned long capacity ){ m_capacity = capacity; // Create the buffer nodes. m_start_ptr = this->allocator->allocate(); // allocate first buffer node BufferNode* ptr = m_start_ptr; for( int i = 0 ; i < this->capacity()-1; i++ ) { BufferNode* p = this->allocator->allocate(); // allocate a buffer node } } My first question: Does this sort of allocation guarantee that the buffer nodes are allocated in contiguous memory locations, i.e. when I try to access the n'th node from address m_start_ptr + n*sizeof(BufferNode) in my Read() method would it work? If not, what's a better way to keep the nodes, creating a linked list? My test harness is the following: // Define an STL compatible allocator of ints that allocates from the managed_shared_memory. // This allocator will allow placing containers in the segment typedef allocator<int, managed_shared_memory::segment_manager> ShmemAllocator; //Alias a vector that uses the previous STL-like allocator so that allocates //its values from the segment typedef SharedMemoryBuffer<int, ShmemAllocator> MyBuf; int main(int argc, char *argv[]) { shared_memory_object::remove("MySharedMemory"); //Create a new segment with given name and size managed_shared_memory segment(create_only, "MySharedMemory", 65536); //Initialize shared memory STL-compatible allocator const ShmemAllocator alloc_inst (segment.get_segment_manager()); //Construct a buffer named "MyBuffer" in shared memory with argument alloc_inst MyBuf *pBuf = segment.construct<MyBuf>("MyBuffer")(100, alloc_inst); } This gives me all kinds of compilation errors related to templates for the last statement. What am I doing wrong?

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• Buying replacement Macbook Pro Battery - Genuine vs. eBay

  - by Nicolas Webb

  I'm looking to replace my Macbook Pro's battery (15", last model before the Unibody). It's currently at 55% capacity (as reported in System Information and Battery Health Monitor). I've reset the SMC firmware, calibrated the battery, and it's just not lasting that long anymore. I've seen some genuine replacements that are "pulls" (pulled from used computers) that are rated at least 90% capacity (iFixit, MacSales). I've also seen a variety of batteries on eBay that look more like clones than genuine batteries, but are new. A new battery from Apple is $129, and when I brought my laptop in they ran the Battery test and said if I bought the battery right then they'd give me a discount (around $100). Anyone out there used one of these "OEM Compatible" batteries? Fit/finish good? (I don't want a funky color or a corner that sticks out.) Or, should I just suck it up and get the genuine replacement (for about twice the price)?

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• growing EBS RAID volume

  - by Ryan Fernandes

  I've created a RAID0 configuration with two 1GB EBS volumes, mounted at /dev/md0 using mdadm and formatted with XFS Next, I copied some files over to fill the volume to around 30% of its capacity (of 2GB) I then created snapshots of the volumes using ec2-consistent-snapshot and created volumes of the said snapshots but specified the volume size to be 2GB (effective doubling the capacity on each disk) I then spun up a new instance, assembled the RAID0 configuration on /dev/md0 from the 2 volumes mentioned above and mount it to /vol df -hT showed /vol as 2GB (as expected) Now I ran sudo xfs_growfs -d /vol. The command completed normally but reported blocks changed from 523776 to 524160 (only!) and df -hT still showed /vol as 2GB (instead of the expected 4GB) I rebooted, remounted, reassembled the RAID but it still reports the old size. Any clue as to what went wrong?

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• Linux user that can read-only all files?

  - by ToiletOverflow

  Is it possible to create a user in Linux/Unix that can see all files on the system, but in a read-only capacity?

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• Macbook pro asks me to "Service Battery"

  - by Uwe Honekamp

  A couple of weeks ago I checked the battery and at that point in time (after 160 load cycles) it still had a capacity of 5000 mAh. Today, my 2006 macbook pro tells me via the battery menu to "Service Battery". According to Coconut Battery the current capacity is only 1590 mAh. The corresponding help text suggests contacting an Apple Authorized Service Provider (AASP) to have the computer checked. Before I decide to throw money at the AASP I'd like to understand what the AASP could possibly do to eliminate the problem. Isn't it more likely that the battery simply broke at 160 cycles and needs to be replaced? Are there any means by software or firmware to influence battery behavior? Of course, the computer hardware might be broken but how could this result in the described effect? And yes, I'm currently trying a calibration cycle but I have some doubts that it will save the day.

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• Slow Windows Explorer on Windows 7

  - by MadBoy

  I have Laptop with i7 (4 cores), 8GB ram and SSD OCZ Vertex 3 MaxIOPS which in testing that I did just now does 400mb/s+ read/write. However the responsiveness of Windows Explorer is far from being perfect. Opening up Computer, Documents, going into folders is very slow (1-5seconds). I don't have any viruses or spyware and I have tried changing properties to optimize view for General Items. I tried disabling Search Indexer but it made search in Outlook 2010 crawl and didn't bring any other effect. Even double clicking on file takes some time to open things up (like clicking a Word document). I don't have any drives mapped, my computer is not joined to domain. I have multiple VPN connections that I connect to but they all have disabled default gateways. I tried using CC Cleaner or some Windows 7 Tweaks app to disable some things. I am power user using Visual Studio, Tortoise SVN and other developer/administration apps. Any non obvious ideas? Edit: So I've been trying to pinpoint where the issue comes from and it seems that straight after reboot Windows Explorer opens very fast, when I load 3-4 programs (Royal TS, Visual Studio, Outlook) it's noticeably slower and the more programs I have it gets worse. After I start closing programs it starts working better and if I leave 2 open it's fast again. I tried doing some research with DiskMon and other programs from sysinternals but couldn't find anything suspicious. Below are stats during normal usage with a lots of programs open: - Ram usage with a lot of programs open and no swap file (i disabled it for testing): 6.95GB - CPU usage: 15%, none of the cores takes more then 50% (I have VS 2010 open x 4) HD Tune Pro: OCZ-VERTEX3 MI Benchmark Test capacity: full Read transfer rate Transfer Rate Minimum : 363.9 MB/s Transfer Rate Maximum : 505.5 MB/s Transfer Rate Average : Access Time : Burst Rate : CPU Usage : HD Tune Pro: OCZ-VERTEX3 MI File Benchmark Drive C: Transfer rate test File Size: 500 MB Sequential read 484102 KB/s Sequential write 444714 KB/s Random read 7779 IOPS Random write 16888 IOPS Random read (queue depth = 32) 73007 IOPS Random write (queue depth = 32) 69790 IOPS HD Tune Pro: OCZ-VERTEX3 MI Random Access Test capacity: full Read test Transfer size operations / sec avg. access time max. access time avg. speed 512 bytes 3260 IOPS 0.306 ms 2.106 ms 1.592 MB/s 4 KB 4161 IOPS 0.240 ms 2.006 ms 16.256 MB/s 64 KB 2382 IOPS 0.419 ms 2.367 ms 148.934 MB/s 1 MB 449 IOPS 2.225 ms 4.197 ms 449.407 MB/s Random 809 IOPS 1.235 ms 6.551 ms 410.527 MB/s HD Tune Pro: OCZ-VERTEX3 MI Extra Tests Test capacity: full Random seek 3975 IOPS 0.252 ms 1.941 MB/s Random seek 4 KB 4245 IOPS 0.236 ms 16.583 MB/s Butterfly seek 4086 IOPS 0.245 ms 1.995 MB/s Random seek / size 64 KB 3812 IOPS 0.262 ms 58.606 MB/s Random seek / size 8 MB 120 IOPS 8.348 ms 485.737 MB/s Sequential outer 4524 IOPS 0.221 ms 282.721 MB/s Sequential middle 4429 IOPS 0.226 ms 276.818 MB/s Sequential inner 5504 IOPS 0.182 ms 344.000 MB/s Burst rate 4472 IOPS 0.224 ms 279.475 MB/s

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• Is it a good idea to have the operating system on a solid state drive?

  - by Kenji Kina

  There is something I don't quite understand. I know a SSD helps with OS load times, but I'm not sure if all this boost is only noticeable/interesting when booting, or gives an all around considerably better experience thereafter. I am interested in having a quick and responsive environment after booting, which leads me to think that it'd be better to spend the SSD capacity in my most used apps (and the page file? Another inside question) and not the OS itself. This, of course, means that I don't know just how much the OS reads/writes its files during normal usage. So, how good an idea is it to dump the whole 20GB+ of Windows 7 OS into the SSD (considering the hefty price per GB of SSD capacity) if I can put up with the usual hard disk boot times? Would I be missing on a lot if I didn't?

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• Is it safe to buy a replacement laptop battery that has slightly different voltage than the original?

  - by Hugoagogo

  I'm looking for a new battery for my Acer Aspire 4741g laptop. I am trying to get a higher capacity battery. Many sites (like this one and this one) list batteries that are interchangeable with the battery that came with the laptop (AS10D41). These batteries have higher capacity, but also marginally lower voltage (11.1V vs. 11.8V). Is this a problem? Does it mean that the battery is actually incompatible? The replacement battery I am looking at is AS10G3E, and is listed in many places as being compatible with the AS10D41, but nobody makes any mention of the differing voltages. I am trying to find out what kind of problems a lower voltage battery can cause. I know P=IV; with reduced voltage, will the machine draw more current, possibly damaging components? I'm just speculating, but I'm worried about the chance that using a battery at a lower voltage will damage my laptop.

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• Is it safe to use consumer MLC SSDs in a server?

  - by Zypher

  We (and by we I mean Jeff) are looking into the possibility of using Consumer MLC SSD disks in our backup data center. We want to try to keep costs down and usable space up - so the Intel X25-E's are pretty much out at about 700$ each and 64GB of capacity. What we are thinking of doing is to buy some of the lower end SSD's that offer more capacity at a lower price point. My boss doesn't think spending about 5k for disks in servers running out of the backup data center is worth the investment. Just how dangerous of an approach is this and what can be done to mitigate these dangers?

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• How much space do NTFS hardlinks/symlinks occupy?

  - by Felix Dombek

  Well, I guess it must be something proportional to the original filename plus the new filename for symlinks, and only the new filename for hardlinks, but how does this affect the disk space exactly? I just made a folder with about a hundred thousand symbolic links in it, and the folder still reported 0 bytes usage. I may be mistaken, but I even think the free capacity of the drive remained the same. Then I permanently deleted the folder and the sizes still stayed the same. Could I fill up a hard disk just with symlinks? Or does NTFS have limitations in that no more than x symlinks are allowed on one drive/in one folder, so the capacity of the drive cannot be reached?

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• growing EBS RAID volume

  - by Ryan Fernandes

  I've created a RAID0 configuration with two 1GB EBS volumes, mounted at /dev/md0 using mdadm and formatted with XFS Next, I copied some files over to fill the volume to around 30% of its capacity (of 2GB) I then created snapshots of the volumes using ec2-consistent-snapshot and created volumes of the said snapshots but specified the volume size to be 2GB (effective doubling the capacity on each disk) I then spun up a new instance, assembled the RAID0 configuration on /dev/md0 from the 2 volumes mentioned above and mount it to /vol df -hT showed /vol as 2GB (as expected) Now I ran sudo xfs_growfs -d /vol. The command completed normally but reported blocks changed from 523776 to 524160 (only!) and df -hT still showed /vol as 2GB (instead of the expected 4GB) I rebooted, remounted, reassembled the RAID but it still reports the old size. EDIT: trying to grow the RAID using mdadm --grow yields mdadm: raid0 array /dev/md0 cannot be reshaped Is there any other way I can grow a RAID0 array?

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