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• The blocking nature of aggregates

  - by Rob Farley

  I wrote a post recently about how query tuning isn’t just about how quickly the query runs – that if you have something (such as SSIS) that is consuming your data (and probably introducing a bottleneck), then it might be more important to have a query which focuses on getting the first bit of data out. You can read that post here.  In particular, we looked at two operators that could be used to ensure that a query returns only Distinct rows. and The Sort operator pulls in all the data, sorts it (discarding duplicates), and then pushes out the remaining rows. The Hash Match operator performs a Hashing function on each row as it comes in, and then looks to see if it’s created a Hash it’s seen before. If not, it pushes the row out. The Sort method is quicker, but has to wait until it’s gathered all the data before it can do the sort, and therefore blocks the data flow. But that was my last post. This one’s a bit different. This post is going to look at how Aggregate functions work, which ties nicely into this month’s T-SQL Tuesday. I’ve frequently explained about the fact that DISTINCT and GROUP BY are essentially the same function, although DISTINCT is the poorer cousin because you have less control over it, and you can’t apply aggregate functions. Just like the operators used for Distinct, there are different flavours of Aggregate operators – coming in blocking and non-blocking varieties. The example I like to use to explain this is a pile of playing cards. If I’m handed a pile of cards and asked to count how many cards there are in each suit, it’s going to help if the cards are already ordered. Suppose I’m playing a game of Bridge, I can easily glance at my hand and count how many there are in each suit, because I keep the pile of cards in order. Moving from left to right, I could tell you I have four Hearts in my hand, even before I’ve got to the end. By telling you that I have four Hearts as soon as I know, I demonstrate the principle of a non-blocking operation. This is known as a Stream Aggregate operation. It requires input which is sorted by whichever columns the grouping is on, and it will release a row as soon as the group changes – when I encounter a Spade, I know I don’t have any more Hearts in my hand. Alternatively, if the pile of cards are not sorted, I won’t know how many Hearts I have until I’ve looked through all the cards. In fact, to count them, I basically need to put them into little piles, and when I’ve finished making all those piles, I can count how many there are in each. Because I don’t know any of the final numbers until I’ve seen all the cards, this is blocking. This performs the aggregate function using a Hash Match. Observant readers will remember this from my Distinct example. You might remember that my earlier Hash Match operation – used for Distinct Flow – wasn’t blocking. But this one is. They’re essentially doing a similar operation, applying a Hash function to some data and seeing if the set of values have been seen before, but before, it needs more information than the mere existence of a new set of values, it needs to consider how many of them there are. A lot is dependent here on whether the data coming out of the source is sorted or not, and this is largely determined by the indexes that are being used. If you look in the Properties of an Index Scan, you’ll be able to see whether the order of the data is required by the plan. A property called Ordered will demonstrate this. In this particular example, the second plan is significantly faster, but is dependent on having ordered data. In fact, if I force a Stream Aggregate on unordered data (which I’m doing by telling it to use a different index), a Sort operation is needed, which makes my plan a lot slower. This is all very straight-forward stuff, and information that most people are fully aware of. I’m sure you’ve all read my good friend Paul White (@sql_kiwi)’s post on how the Query Optimizer chooses which type of aggregate function to apply. But let’s take a look at SQL Server Integration Services. SSIS gives us a Aggregate transformation for use in Data Flow Tasks, but it’s described as Blocking. The definitive article on Performance Tuning SSIS uses Sort and Aggregate as examples of Blocking Transformations. I’ve just shown you that Aggregate operations used by the Query Optimizer are not always blocking, but that the SSIS Aggregate component is an example of a blocking transformation. But is it always the case? After all, there are plenty of SSIS Performance Tuning talks out there that describe the value of sorted data in Data Flow Tasks, describing the IsSorted property that can be set through the Advanced Editor of your Source component. And so I set about testing the Aggregate transformation in SSIS, to prove for sure whether providing Sorted data would let the Aggregate transform behave like a Stream Aggregate. (Of course, I knew the answer already, but it helps to be able to demonstrate these things). A query that will produce a million rows in order was in order. Let me rephrase. I used a query which produced the numbers from 1 to 1000000, in a single field, ordered. The IsSorted flag was set on the source output, with the only column as SortKey 1. Performing an Aggregate function over this (counting the number of rows per distinct number) should produce an additional column with 1 in it. If this were being done in T-SQL, the ordered data would allow a Stream Aggregate to be used. In fact, if the Query Optimizer saw that the field had a Unique Index on it, it would be able to skip the Aggregate function completely, and just insert the value 1. This is a shortcut I wouldn’t be expecting from SSIS, but certainly the Stream behaviour would be nice. Unfortunately, it’s not the case. As you can see from the screenshots above, the data is pouring into the Aggregate function, and not being released until all million rows have been seen. It’s not doing a Stream Aggregate at all. This is expected behaviour. (I put that in bold, because I want you to realise this.) An SSIS transformation is a piece of code that runs. It’s a physical operation. When you write T-SQL and ask for an aggregation to be done, it’s a logical operation. The physical operation is either a Stream Aggregate or a Hash Match. In SSIS, you’re telling the system that you want a generic Aggregation, that will have to work with whatever data is passed in. I’m not saying that it wouldn’t be possible to make a sometimes-blocking aggregation component in SSIS. A Custom Component could be created which could detect whether the SortKeys columns of the input matched the Grouping columns of the Aggregation, and either call the blocking code or the non-blocking code as appropriate. One day I’ll make one of those, and publish it on my blog. I’ve done it before with a Script Component, but as Script components are single-use, I was able to handle the data knowing everything about my data flow already. As per my previous post – there are a lot of aspects in which tuning SSIS and tuning execution plans use similar concepts. In both situations, it really helps to have a feel for what’s going on behind the scenes. Considering whether an operation is blocking or not is extremely relevant to performance, and that it’s not always obvious from the surface. In a future post, I’ll show the impact of blocking v non-blocking and synchronous v asynchronous components in SSIS, using some of LobsterPot’s Script Components and Custom Components as examples. When I get that sorted, I’ll make a Stream Aggregate component available for download.

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• I see no LOBs!

  - by Paul White

  Is it possible to see LOB (large object) logical reads from STATISTICS IO output on a table with no LOB columns? I was asked this question today by someone who had spent a good fraction of their afternoon trying to work out why this was occurring – even going so far as to re-run DBCC CHECKDB to see if any corruption had taken place.  The table in question wasn’t particularly pretty – it had grown somewhat organically over time, with new columns being added every so often as the need arose.  Nevertheless, it remained a simple structure with no LOB columns – no TEXT or IMAGE, no XML, no MAX types – nothing aside from ordinary INT, MONEY, VARCHAR, and DATETIME types.  To add to the air of mystery, not every query that ran against the table would report LOB logical reads – just sometimes – but when it did, the query often took much longer to execute. Ok, enough of the pre-amble.  I can’t reproduce the exact structure here, but the following script creates a table that will serve to demonstrate the effect: IF OBJECT_ID(N'dbo.Test', N'U') IS NOT NULL DROP TABLE dbo.Test GO CREATE TABLE dbo.Test ( row_id NUMERIC IDENTITY NOT NULL,   col01 NVARCHAR(450) NOT NULL, col02 NVARCHAR(450) NOT NULL, col03 NVARCHAR(450) NOT NULL, col04 NVARCHAR(450) NOT NULL, col05 NVARCHAR(450) NOT NULL, col06 NVARCHAR(450) NOT NULL, col07 NVARCHAR(450) NOT NULL, col08 NVARCHAR(450) NOT NULL, col09 NVARCHAR(450) NOT NULL, col10 NVARCHAR(450) NOT NULL, CONSTRAINT [PK dbo.Test row_id] PRIMARY KEY CLUSTERED (row_id) ) ; The next script loads the ten variable-length character columns with one-character strings in the first row, two-character strings in the second row, and so on down to the 450th row: WITH Numbers AS ( -- Generates numbers 1 - 450 inclusive SELECT TOP (450) n = ROW_NUMBER() OVER (ORDER BY (SELECT 0)) FROM master.sys.columns C1, master.sys.columns C2, master.sys.columns C3 ORDER BY n ASC ) INSERT dbo.Test WITH (TABLOCKX) SELECT REPLICATE(N'A', N.n), REPLICATE(N'B', N.n), REPLICATE(N'C', N.n), REPLICATE(N'D', N.n), REPLICATE(N'E', N.n), REPLICATE(N'F', N.n), REPLICATE(N'G', N.n), REPLICATE(N'H', N.n), REPLICATE(N'I', N.n), REPLICATE(N'J', N.n) FROM Numbers AS N ORDER BY N.n ASC ; Once those two scripts have run, the table contains 450 rows and 10 columns of data like this: Most of the time, when we query data from this table, we don’t see any LOB logical reads, for example: -- Find the maximum length of the data in -- column 5 for a range of rows SELECT result = MAX(DATALENGTH(T.col05)) FROM dbo.Test AS T WHERE row_id BETWEEN 50 AND 100 ; But with a different query… -- Read all the data in column 1 SELECT result = MAX(DATALENGTH(T.col01)) FROM dbo.Test AS T ; …suddenly we have 49 LOB logical reads, as well as the ‘normal’ logical reads we would expect. The Explanation If we had tried to create this table in SQL Server 2000, we would have received a warning message to say that future INSERT or UPDATE operations on the table might fail if the resulting row exceeded the in-row storage limit of 8060 bytes.  If we needed to store more data than would fit in an 8060 byte row (including internal overhead) we had to use a LOB column – TEXT, NTEXT, or IMAGE.  These special data types store the large data values in a separate structure, with just a small pointer left in the original row. Row Overflow SQL Server 2005 introduced a feature called row overflow, which allows one or more variable-length columns in a row to move to off-row storage if the data in a particular row would otherwise exceed 8060 bytes.  You no longer receive a warning when creating (or altering) a table that might need more than 8060 bytes of in-row storage; if SQL Server finds that it can no longer fit a variable-length column in a particular row, it will silently move one or more of these columns off the row into a separate allocation unit. Only variable-length columns can be moved in this way (for example the (N)VARCHAR, VARBINARY, and SQL_VARIANT types).  Fixed-length columns (like INTEGER and DATETIME for example) never move into ‘row overflow’ storage.  The decision to move a column off-row is done on a row-by-row basis – so data in a particular column might be stored in-row for some table records, and off-row for others. In general, if SQL Server finds that it needs to move a column into row-overflow storage, it moves the largest variable-length column record for that row.  Note that in the case of an UPDATE statement that results in the 8060 byte limit being exceeded, it might not be the column that grew that is moved! Sneaky LOBs Anyway, that’s all very interesting but I don’t want to get too carried away with the intricacies of row-overflow storage internals.  The point is that it is now possible to define a table with non-LOB columns that will silently exceed the old row-size limit and result in ordinary variable-length columns being moved to off-row storage.  Adding new columns to a table, expanding an existing column definition, or simply storing more data in a column than you used to – all these things can result in one or more variable-length columns being moved off the row. Note that row-overflow storage is logically quite different from old-style LOB and new-style MAX data type storage – individual variable-length columns are still limited to 8000 bytes each – you can just have more of them now.  Having said that, the physical mechanisms involved are very similar to full LOB storage – a column moved to row-overflow leaves a 24-byte pointer record in the row, and the ‘separate storage’ I have been talking about is structured very similarly to both old-style LOBs and new-style MAX types.  The disadvantages are also the same: when SQL Server needs a row-overflow column value it needs to follow the in-row pointer a navigate another chain of pages, just like retrieving a traditional LOB. And Finally… In the example script presented above, the rows with row_id values from 402 to 450 inclusive all exceed the total in-row storage limit of 8060 bytes.  A SELECT that references a column in one of those rows that has moved to off-row storage will incur one or more lob logical reads as the storage engine locates the data.  The results on your system might vary slightly depending on your settings, of course; but in my tests only column 1 in rows 402-450 moved off-row.  You might like to play around with the script – updating columns, changing data type lengths, and so on – to see the effect on lob logical reads and which columns get moved when.  You might even see row-overflow columns moving back in-row if they are updated to be smaller (hint: reduce the size of a column entry by at least 1000 bytes if you hope to see this). Be aware that SQL Server will not warn you when it moves ‘ordinary’ variable-length columns into overflow storage, and it can have dramatic effects on performance.  It makes more sense than ever to choose column data types sensibly.  If you make every column a VARCHAR(8000) or NVARCHAR(4000), and someone stores data that results in a row needing more than 8060 bytes, SQL Server might turn some of your column data into pseudo-LOBs – all without saying a word. Finally, some people make a distinction between ordinary LOBs (those that can hold up to 2GB of data) and the LOB-like structures created by row-overflow (where columns are still limited to 8000 bytes) by referring to row-overflow LOBs as SLOBs.  I find that quite appealing, but the ‘S’ stands for ‘small’, which makes expanding the whole acronym a little daft-sounding…small large objects anyone? © Paul White 2011 email: [email protected] twitter: @SQL_Kiwi

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• Restoring databases to a set drive and directory

  - by okeofs

   Restoring databases to a set drive and directory Introduction Often people say that necessity is the mother of invention. In this case I was faced with the dilemma of having to restore several databases, with multiple ‘ndf’ files, and having to restore them with different physical file names, drives and directories on servers other than the servers from which they originated. As most of us would do, I went to Google to see if I could find some code to achieve this task and found some interesting snippets on Pinal Dave’s website. Naturally, I had to take it further than the code snippet, HOWEVER it was a great place to start. Creating a temp table to hold database file details First off, I created a temp table which would hold the details of the individual data files within the database. Although there are a plethora of fields (within the temp table below), I utilize LogicalName only within this example. The temporary table structure may be seen below:   create table #tmp ( LogicalName nvarchar(128)  ,PhysicalName nvarchar(260)  ,Type char(1)  ,FileGroupName nvarchar(128)  ,Size numeric(20,0)  ,MaxSize numeric(20,0), Fileid tinyint, CreateLSN numeric(25,0), DropLSN numeric(25, 0), UniqueID uniqueidentifier, ReadOnlyLSN numeric(25,0), ReadWriteLSN numeric(25,0), BackupSizeInBytes bigint, SourceBlocSize int, FileGroupId int, LogGroupGUID uniqueidentifier, DifferentialBaseLSN numeric(25,0), DifferentialBaseGUID uniqueidentifier, IsReadOnly bit, IsPresent bit,  TDEThumbPrint varchar(50) )    We now declare and populate a variable(@path), setting the variable to the path to our SOURCE database backup. declare @path varchar(50) set @path = 'P:\DATA\MYDATABASE.bak'   From this point, we insert the file details of our database into the temp table. Note that we do so by utilizing a restore statement HOWEVER doing so in ‘filelistonly’ mode.   insert #tmp EXEC ('restore filelistonly from disk = ''' + @path + '''')   At this point, I depart from what I gleaned from Pinal Dave.   I now instantiate a few more local variables. The use of each variable will be evident within the cursor (which follows):   Declare @RestoreString as Varchar(max) Declare @NRestoreString as NVarchar(max) Declare @LogicalName  as varchar(75) Declare @counter as int Declare @rows as int set @counter = 1 select @rows = COUNT(*) from #tmp  -- Count the number of records in the temp                                    -- table   Declaring and populating the cursor At this point I do realize that many people are cringing about the use of a cursor. Being an Oracle professional as well, I have learnt that there is a time and place for cursors. I would remind the reader that the data that will be read into the cursor is from a local temp table and as such, any locking of the records (within the temp table) is not really an issue.   DECLARE MY_CURSOR Cursor  FOR  Select LogicalName  From #tmp   Parsing the logical names from within the cursor. A small caveat that works in our favour,  is that the first logical name (of our database) is the logical name of the primary data file (.mdf). Other files, except for the very last logical name, belong to secondary data files. The last logical name is that of our database log file.   I now open my cursor and populate the variable @RestoreString Open My_Cursor  set @RestoreString =  'RESTORE DATABASE [MYDATABASE] FROM DISK = N''P:\DATA\ MYDATABASE.bak''' + ' with  '   We now fetch the first record from the temp table.   Fetch NEXT FROM MY_Cursor INTO @LogicalName   While there are STILL records left within the cursor, we dynamically build our restore string. Note that we are using concatenation to create ‘one big restore executable string’.   Note also that the target physical file name is hardwired, as is the target directory.   While (@@FETCH_STATUS <> -1) BEGIN IF (@@FETCH_STATUS <> -2) -- As long as there are no rows missing select @RestoreString = case  when @counter = 1 then -- This is the mdf file    @RestoreString + 'move  N''' + @LogicalName + '''' + ' TO N’’X:\DATA1\'+ @LogicalName + '.mdf' + '''' + ', '   -- OK, if it passes through here we are dealing with an .ndf file -- Note that Counter must be greater than 1 and less than the number of rows.   when @counter > 1 and @counter < @rows then -- These are the ndf file(s)    @RestoreString + 'move  N''' + @LogicalName + '''' + ' TO N’’X:\DATA1\'+ @LogicalName + '.ndf' + '''' + ', '   -- OK, if it passes through here we are dealing with the log file When @LogicalName like '%log%' then    @RestoreString + 'move  N''' + @LogicalName + '''' + ' TO N’’X:\DATA1\'+ @LogicalName + '.ldf' +'''' end --Increment the counter   set @counter = @counter + 1 FETCH NEXT FROM MY_CURSOR INTO @LogicalName END   At this point we have populated the varchar(max) variable @RestoreString with a concatenation of all the necessary file names. What we now need to do is to run the sp_executesql stored procedure, to effect the restore.   First, we must place our ‘concatenated string’ into an nvarchar based variable. Obviously this will only work as long as the length of @RestoreString is less than varchar(max) / 2.   set @NRestoreString = @RestoreString EXEC sp_executesql @NRestoreString   Upon completion of this step, the database should be restored to the server. I now close and deallocate the cursor, and to be clean, I would also drop my temp table.   CLOSE MY_CURSOR DEALLOCATE MY_CURSOR GO   Conclusion Restoration of databases on different servers with different physical names and on different drives are a fact of life. Through the use of a few variables and a simple cursor, we may achieve an efficient and effective way to achieve this task.

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• SQL Server &ndash; Undelete a Table and Restore a Single Table from Backup

  - by Mladen Prajdic

  This post is part of the monthly community event called T-SQL Tuesday started by Adam Machanic (blog|twitter) and hosted by someone else each month. This month the host is Sankar Reddy (blog|twitter) and the topic is Misconceptions in SQL Server. You can follow posts for this theme on Twitter by looking at #TSQL2sDay hashtag. Let me start by saying: This code is a crazy hack that is to never be used unless you really, really have to. Really! And I don’t think there’s a time when you would really have to use it for real. Because it’s a hack there are number of things that can go wrong so play with it knowing that. I’ve managed to totally corrupt one database. :) Oh… and for those saying: yeah yeah.. you have a single table in a file group and you’re restoring that, I say “nay nay” to you. As we all know SQL Server can’t do single table restores from backup. This is kind of a obvious thing due to different relational integrity (RI) concerns. Since we have to maintain that we have to restore all tables represented in a RI graph. For this exercise i say BAH! to those concerns. Note that this method “works” only for simple tables that don’t have LOB and off rows data. The code can be expanded to include those but I’ve tried to leave things “simple”. Note that for this to work our table needs to be relatively static data-wise. This doesn’t work for OLTP table. Products are a perfect example of static data. They don’t change much between backups, pretty much everything depends on them and their table is one of those tables that are relatively easy to accidentally delete everything from. This only works if the database is in Full or Bulk-Logged recovery mode for tables where the contents have been deleted or truncated but NOT when a table was dropped. Everything we’ll talk about has to be done before the data pages are reused for other purposes. After deletion or truncation the pages are marked as reusable so you have to act fast. The best thing probably is to put the database into single user mode ASAP while you’re performing this procedure and return it to multi user after you’re done. How do we do it? We will be using an undocumented but known DBCC commands: DBCC PAGE, an undocumented function sys.fn_dblog and a little known DATABASE RESTORE PAGE option. All tests will be on a copy of Production.Product table in AdventureWorks database called Production.Product1 because the original table has FK constraints that prevent us from truncating it for testing. -- create a duplicate table. This doesn't preserve indexes!SELECT *INTO AdventureWorks.Production.Product1FROM AdventureWorks.Production.Product   After we run this code take a full back to perform further testing.   First let’s see what the difference between DELETE and TRUNCATE is when it comes to logging. With DELETE every row deletion is logged in the transaction log. With TRUNCATE only whole data page deallocations are logged in the transaction log. Getting deleted data pages is simple. All we have to look for is row delete entry in the sys.fn_dblog output. But getting data pages that were truncated from the transaction log presents a bit of an interesting problem. I will not go into depths of IAM(Index Allocation Map) and PFS (Page Free Space) pages but suffice to say that every IAM page has intervals that tell us which data pages are allocated for a table and which aren’t. If we deep dive into the sys.fn_dblog output we can see that once you truncate a table all the pages in all the intervals are deallocated and this is shown in the PFS page transaction log entry as deallocation of pages. For every 8 pages in the same extent there is one PFS page row in the transaction log. This row holds information about all 8 pages in CSV format which means we can get to this data with some parsing. A great help for parsing this stuff is Peter Debetta’s handy function dbo.HexStrToVarBin that converts hexadecimal string into a varbinary value that can be easily converted to integer tus giving us a readable page number. The shortened (columns removed) sys.fn_dblog output for a PFS page with CSV data for 1 extent (8 data pages) looks like this: -- [Page ID] is displayed in hex format. -- To convert it to readable int we'll use dbo.HexStrToVarBin function found at -- http://sqlblog.com/blogs/peter_debetta/archive/2007/03/09/t-sql-convert-hex-string-to-varbinary.aspx -- This function must be installed in the master databaseSELECT Context, AllocUnitName, [Page ID], DescriptionFROM sys.fn_dblog(NULL, NULL)WHERE [Current LSN] = '00000031:00000a46:007d' The pages at the end marked with 0x00—> are pages that are allocated in the extent but are not part of a table. We can inspect the raw content of each data page with a DBCC PAGE command: -- we need this trace flag to redirect output to the query window.DBCC TRACEON (3604); -- WITH TABLERESULTS gives us data in table format instead of message format-- we use format option 3 because it's the easiest to read and manipulate further onDBCC PAGE (AdventureWorks, 1, 613, 3) WITH TABLERESULTS   Since the DBACC PAGE output can be quite extensive I won’t put it here. You can see an example of it in the link at the beginning of this section. Getting deleted data back When we run a delete statement every row to be deleted is marked as a ghost record. A background process periodically cleans up those rows. A huge misconception is that the data is actually removed. It’s not. Only the pointers to the rows are removed while the data itself is still on the data page. We just can’t access it with normal means. To get those pointers back we need to restore every deleted page using the RESTORE PAGE option mentioned above. This restore must be done from a full backup, followed by any differential and log backups that you may have. This is necessary to bring the pages up to the same point in time as the rest of the data.  However the restore doesn’t magically connect the restored page back to the original table. It simply replaces the current page with the one from the backup. After the restore we use the DBCC PAGE to read data directly from all data pages and insert that data into a temporary table. To finish the RESTORE PAGE  procedure we finally have to take a tail log backup (simple backup of the transaction log) and restore it back. We can now insert data from the temporary table to our original table by hand. Getting truncated data back When we run a truncate the truncated data pages aren’t touched at all. Even the pointers to rows stay unchanged. Because of this getting data back from truncated table is simple. we just have to find out which pages belonged to our table and use DBCC PAGE to read data off of them. No restore is necessary. Turns out that the problems we had with finding the data pages is alleviated by not having to do a RESTORE PAGE procedure. Stop stalling… show me The Code! This is the code for getting back deleted and truncated data back. It’s commented in all the right places so don’t be afraid to take a closer look. Make sure you have a full backup before trying this out. Also I suggest that the last step of backing and restoring the tail log is performed by hand. USE masterGOIF OBJECT_ID('dbo.HexStrToVarBin') IS NULL RAISERROR ('No dbo.HexStrToVarBin installed. Go to http://sqlblog.com/blogs/peter_debetta/archive/2007/03/09/t-sql-convert-hex-string-to-varbinary.aspx and install it in master database' , 18, 1) SET NOCOUNT ONBEGIN TRY DECLARE @dbName VARCHAR(1000), @schemaName VARCHAR(1000), @tableName VARCHAR(1000), @fullBackupName VARCHAR(1000), @undeletedTableName VARCHAR(1000), @sql VARCHAR(MAX), @tableWasTruncated bit; /* THE FIRST LINE ARE OUR INPUT PARAMETERS In this case we're trying to recover Production.Product1 table in AdventureWorks database. My full backup of AdventureWorks database is at e:\AW.bak */ SELECT @dbName = 'AdventureWorks', @schemaName = 'Production', @tableName = 'Product1', @fullBackupName = 'e:\AW.bak', @undeletedTableName = '##' + @tableName + '_Undeleted', @tableWasTruncated = 0, -- copy the structure from original table to a temp table that we'll fill with restored data @sql = 'IF OBJECT_ID(''tempdb..' + @undeletedTableName + ''') IS NOT NULL DROP TABLE ' + @undeletedTableName + ' SELECT *' + ' INTO ' + @undeletedTableName + ' FROM [' + @dbName + '].[' + @schemaName + '].[' + @tableName + ']' + ' WHERE 1 = 0' EXEC (@sql) IF OBJECT_ID('tempdb..#PagesToRestore') IS NOT NULL DROP TABLE #PagesToRestore /* FIND DATA PAGES WE NEED TO RESTORE*/ CREATE TABLE #PagesToRestore ([ID] INT IDENTITY(1,1), [FileID] INT, [PageID] INT, [SQLtoExec] VARCHAR(1000)) -- DBCC PACE statement to run later RAISERROR ('Looking for deleted pages...', 10, 1) -- use T-LOG direct read to get deleted data pages INSERT INTO #PagesToRestore([FileID], [PageID], [SQLtoExec]) EXEC('USE [' + @dbName + '];SELECT FileID, PageID, ''DBCC TRACEON (3604); DBCC PAGE ([' + @dbName + '], '' + FileID + '', '' + PageID + '', 3) WITH TABLERESULTS'' as SQLToExecFROM (SELECT DISTINCT LEFT([Page ID], 4) AS FileID, CONVERT(VARCHAR(100), ' + 'CONVERT(INT, master.dbo.HexStrToVarBin(SUBSTRING([Page ID], 6, 20)))) AS PageIDFROM sys.fn_dblog(NULL, NULL)WHERE AllocUnitName LIKE ''%' + @schemaName + '.' + @tableName + '%'' ' + 'AND Context IN (''LCX_MARK_AS_GHOST'', ''LCX_HEAP'') AND Operation in (''LOP_DELETE_ROWS''))t');SELECT *FROM #PagesToRestore -- if upper EXEC returns 0 rows it means the table was truncated so find truncated pages IF (SELECT COUNT(*) FROM #PagesToRestore) = 0 BEGIN RAISERROR ('No deleted pages found. Looking for truncated pages...', 10, 1) -- use T-LOG read to get truncated data pages INSERT INTO #PagesToRestore([FileID], [PageID], [SQLtoExec]) -- dark magic happens here -- because truncation simply deallocates pages we have to find out which pages were deallocated. -- we can find this out by looking at the PFS page row's Description column. -- for every deallocated extent the Description has a CSV of 8 pages in that extent. -- then it's just a matter of parsing it. -- we also remove the pages in the extent that weren't allocated to the table itself -- marked with '0x00-->00' EXEC ('USE [' + @dbName + '];DECLARE @truncatedPages TABLE(DeallocatedPages VARCHAR(8000), IsMultipleDeallocs BIT);INSERT INTO @truncatedPagesSELECT REPLACE(REPLACE(Description, ''Deallocated '', ''Y''), ''0x00-->00 '', ''N'') + '';'' AS DeallocatedPages, CHARINDEX('';'', Description) AS IsMultipleDeallocsFROM (SELECT DISTINCT LEFT([Page ID], 4) AS FileID, CONVERT(VARCHAR(100), CONVERT(INT, master.dbo.HexStrToVarBin(SUBSTRING([Page ID], 6, 20)))) AS PageID, DescriptionFROM sys.fn_dblog(NULL, NULL)WHERE Context IN (''LCX_PFS'') AND Description LIKE ''Deallocated%'' AND AllocUnitName LIKE ''%' + @schemaName + '.' + @tableName + '%'') t;SELECT FileID, PageID , ''DBCC TRACEON (3604); DBCC PAGE ([' + @dbName + '], '' + FileID + '', '' + PageID + '', 3) WITH TABLERESULTS'' as SQLToExecFROM (SELECT LEFT(PageAndFile, 1) as WasPageAllocatedToTable , SUBSTRING(PageAndFile, 2, CHARINDEX('':'', PageAndFile) - 2 ) as FileID , CONVERT(VARCHAR(100), CONVERT(INT, master.dbo.HexStrToVarBin(SUBSTRING(PageAndFile, CHARINDEX('':'', PageAndFile) + 1, LEN(PageAndFile))))) as PageIDFROM ( SELECT SUBSTRING(DeallocatedPages, delimPosStart, delimPosEnd - delimPosStart) as PageAndFile, IsMultipleDeallocs FROM ( SELECT *, CHARINDEX('';'', DeallocatedPages)*(N-1) + 1 AS delimPosStart, CHARINDEX('';'', DeallocatedPages)*N AS delimPosEnd FROM @truncatedPages t1 CROSS APPLY (SELECT TOP (case when t1.IsMultipleDeallocs = 1 then 8 else 1 end) ROW_NUMBER() OVER(ORDER BY number) as N FROM master..spt_values) t2 )t)t)tWHERE WasPageAllocatedToTable = ''Y''') SELECT @tableWasTruncated = 1 END DECLARE @lastID INT, @pagesCount INT SELECT @lastID = 1, @pagesCount = COUNT(*) FROM #PagesToRestore SELECT @sql = 'Number of pages to restore: ' + CONVERT(VARCHAR(10), @pagesCount) IF @pagesCount = 0 RAISERROR ('No data pages to restore.', 18, 1) ELSE RAISERROR (@sql, 10, 1) -- If the table was truncated we'll read the data directly from data pages without restoring from backup IF @tableWasTruncated = 0 BEGIN -- RESTORE DATA PAGES FROM FULL BACKUP IN BATCHES OF 200 WHILE @lastID <= @pagesCount BEGIN -- create CSV string of pages to restore SELECT @sql = STUFF((SELECT ',' + CONVERT(VARCHAR(100), FileID) + ':' + CONVERT(VARCHAR(100), PageID) FROM #PagesToRestore WHERE ID BETWEEN @lastID AND @lastID + 200 ORDER BY ID FOR XML PATH('')), 1, 1, '') SELECT @sql = 'RESTORE DATABASE [' + @dbName + '] PAGE = ''' + @sql + ''' FROM DISK = ''' + @fullBackupName + '''' RAISERROR ('Starting RESTORE command:' , 10, 1) WITH NOWAIT; RAISERROR (@sql , 10, 1) WITH NOWAIT; EXEC(@sql); RAISERROR ('Restore DONE' , 10, 1) WITH NOWAIT; SELECT @lastID = @lastID + 200 END /* If you have any differential or transaction log backups you should restore them here to bring the previously restored data pages up to date */ END DECLARE @dbccSinglePage TABLE ( [ParentObject] NVARCHAR(500), [Object] NVARCHAR(500), [Field] NVARCHAR(500), [VALUE] NVARCHAR(MAX) ) DECLARE @cols NVARCHAR(MAX), @paramDefinition NVARCHAR(500), @SQLtoExec VARCHAR(1000), @FileID VARCHAR(100), @PageID VARCHAR(100), @i INT = 1 -- Get deleted table columns from information_schema view -- Need sp_executeSQL because database name can't be passed in as variable SELECT @cols = 'select @cols = STUFF((SELECT '', ['' + COLUMN_NAME + '']''FROM ' + @dbName + '.INFORMATION_SCHEMA.COLUMNSWHERE TABLE_NAME = ''' + @tableName + ''' AND TABLE_SCHEMA = ''' + @schemaName + '''ORDER BY ORDINAL_POSITIONFOR XML PATH('''')), 1, 2, '''')', @paramDefinition = N'@cols nvarchar(max) OUTPUT' EXECUTE sp_executesql @cols, @paramDefinition, @cols = @cols OUTPUT -- Loop through all the restored data pages, -- read data from them and insert them into temp table -- which you can then insert into the orignial deleted table DECLARE dbccPageCursor CURSOR GLOBAL FORWARD_ONLY FOR SELECT [FileID], [PageID], [SQLtoExec] FROM #PagesToRestore ORDER BY [FileID], [PageID] OPEN dbccPageCursor; FETCH NEXT FROM dbccPageCursor INTO @FileID, @PageID, @SQLtoExec; WHILE @@FETCH_STATUS = 0 BEGIN RAISERROR ('---------------------------------------------', 10, 1) WITH NOWAIT; SELECT @sql = 'Loop iteration: ' + CONVERT(VARCHAR(10), @i); RAISERROR (@sql, 10, 1) WITH NOWAIT; SELECT @sql = 'Running: ' + @SQLtoExec RAISERROR (@sql, 10, 1) WITH NOWAIT; -- if something goes wrong with DBCC execution or data gathering, skip it but print error BEGIN TRY INSERT INTO @dbccSinglePage EXEC (@SQLtoExec) -- make the data insert magic happen here IF (SELECT CONVERT(BIGINT, [VALUE]) FROM @dbccSinglePage WHERE [Field] LIKE '%Metadata: ObjectId%') = OBJECT_ID('['+@dbName+'].['+@schemaName +'].['+@tableName+']') BEGIN DELETE @dbccSinglePage WHERE NOT ([ParentObject] LIKE 'Slot % Offset %' AND [Object] LIKE 'Slot % Column %') SELECT @sql = 'USE tempdb; ' + 'IF (OBJECTPROPERTY(object_id(''' + @undeletedTableName + '''), ''TableHasIdentity'') = 1) ' + 'SET IDENTITY_INSERT ' + @undeletedTableName + ' ON; ' + 'INSERT INTO ' + @undeletedTableName + '(' + @cols + ') ' + STUFF((SELECT ' UNION ALL SELECT ' + STUFF((SELECT ', ' + CASE WHEN VALUE = '[NULL]' THEN 'NULL' ELSE '''' + [VALUE] + '''' END FROM ( -- the unicorn help here to correctly set ordinal numbers of columns in a data page -- it's turning STRING order into INT order (1,10,11,2,21 into 1,2,..10,11...21) SELECT [ParentObject], [Object], Field, VALUE, RIGHT('00000' + O1, 6) AS ParentObjectOrder, RIGHT('00000' + REVERSE(LEFT(O2, CHARINDEX(' ', O2)-1)), 6) AS ObjectOrder FROM ( SELECT [ParentObject], [Object], Field, VALUE, REPLACE(LEFT([ParentObject], CHARINDEX('Offset', [ParentObject])-1), 'Slot ', '') AS O1, REVERSE(LEFT([Object], CHARINDEX('Offset ', [Object])-2)) AS O2 FROM @dbccSinglePage WHERE t.ParentObject = ParentObject )t)t ORDER BY ParentObjectOrder, ObjectOrder FOR XML PATH('')), 1, 2, '') FROM @dbccSinglePage t GROUP BY ParentObject FOR XML PATH('') ), 1, 11, '') + ';' RAISERROR (@sql, 10, 1) WITH NOWAIT; EXEC (@sql) END END TRY BEGIN CATCH SELECT @sql = 'ERROR!!!' + CHAR(10) + CHAR(13) + 'ErrorNumber: ' + ERROR_NUMBER() + '; ErrorMessage' + ERROR_MESSAGE() + CHAR(10) + CHAR(13) + 'FileID: ' + @FileID + '; PageID: ' + @PageID RAISERROR (@sql, 10, 1) WITH NOWAIT; END CATCH DELETE @dbccSinglePage SELECT @sql = 'Pages left to process: ' + CONVERT(VARCHAR(10), @pagesCount - @i) + CHAR(10) + CHAR(13) + CHAR(10) + CHAR(13) + CHAR(10) + CHAR(13), @i = @i+1 RAISERROR (@sql, 10, 1) WITH NOWAIT; FETCH NEXT FROM dbccPageCursor INTO @FileID, @PageID, @SQLtoExec; END CLOSE dbccPageCursor; DEALLOCATE dbccPageCursor; EXEC ('SELECT ''' + @undeletedTableName + ''' as TableName; SELECT * FROM ' + @undeletedTableName)END TRYBEGIN CATCH SELECT ERROR_NUMBER() AS ErrorNumber, ERROR_MESSAGE() AS ErrorMessage IF CURSOR_STATUS ('global', 'dbccPageCursor') >= 0 BEGIN CLOSE dbccPageCursor; DEALLOCATE dbccPageCursor; ENDEND CATCH-- if the table was deleted we need to finish the restore page sequenceIF @tableWasTruncated = 0BEGIN -- take a log tail backup and then restore it to complete page restore process DECLARE @currentDate VARCHAR(30) SELECT @currentDate = CONVERT(VARCHAR(30), GETDATE(), 112) RAISERROR ('Starting Log Tail backup to c:\Temp ...', 10, 1) WITH NOWAIT; PRINT ('BACKUP LOG [' + @dbName + '] TO DISK = ''c:\Temp\' + @dbName + '_TailLogBackup_' + @currentDate + '.trn''') EXEC ('BACKUP LOG [' + @dbName + '] TO DISK = ''c:\Temp\' + @dbName + '_TailLogBackup_' + @currentDate + '.trn''') RAISERROR ('Log Tail backup done.', 10, 1) WITH NOWAIT; RAISERROR ('Starting Log Tail restore from c:\Temp ...', 10, 1) WITH NOWAIT; PRINT ('RESTORE LOG [' + @dbName + '] FROM DISK = ''c:\Temp\' + @dbName + '_TailLogBackup_' + @currentDate + '.trn''') EXEC ('RESTORE LOG [' + @dbName + '] FROM DISK = ''c:\Temp\' + @dbName + '_TailLogBackup_' + @currentDate + '.trn''') RAISERROR ('Log Tail restore done.', 10, 1) WITH NOWAIT;END-- The last step is manual. Insert data from our temporary table to the original deleted table The misconception here is that you can do a single table restore properly in SQL Server. You can't. But with little experimentation you can get pretty close to it. One way to possible remove a dependency on a backup to retrieve deleted pages is to quickly run a similar script to the upper one that gets data directly from data pages while the rows are still marked as ghost records. It could be done if we could beat the ghost record cleanup task.

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• ?Oracle Database 12c????Information Lifecycle Management ILM?Storage Enhancements

  - by Liu Maclean(???)

  Oracle Database 12c????Information Lifecycle Management ILM ?????????Storage Enhancements ???????? Lifecycle Management ILM ????????? Automatic Data Placement ??????, ??ADP? ?????? 12c???????Datafile??? Online Move Datafile, ????????????????datafile???????,??????????????? ????(12.1.0.1)Automatic Data Optimization?heat map????????: ????????? (CDB)?????Automatic Data Optimization?heat map Row-level policies for ADO are not supported for Temporal Validity. Partition-level ADO and compression are supported if partitioned on the end-time columns. Row-level policies for ADO are not supported for in-database archiving. Partition-level ADO and compression are supported if partitioned on the ORA_ARCHIVE_STATE column. Custom policies (user-defined functions) for ADO are not supported if the policies default at the tablespace level. ADO does not perform checks for storage space in a target tablespace when using storage tiering. ADO is not supported on tables with object types or materialized views. ADO concurrency (the number of simultaneous policy jobs for ADO) depends on the concurrency of the Oracle scheduler. If a policy job for ADO fails more than two times, then the job is marked disabled and the job must be manually enabled later. Policies for ADO are only run in the Oracle Scheduler maintenance windows. Outside of the maintenance windows all policies are stopped. The only exceptions are those jobs for rebuilding indexes in ADO offline mode. ADO has restrictions related to moving tables and table partitions. ??????row,segment???????????ADO??,?????create table?alter table?????? ????ADO??,??????????????,???????????????? storage tier , ?????????storage tier?????????, ??????????????ADO??????????? segment?row??group? ?CREATE TABLE?ALERT TABLE???ILM???,??????????????????ADO policy? ??ILM policy???????????????? ??????? ????ADO policy, ?????alter table  ???????,?????????????? CREATE TABLE sales_ado (PROD_ID NUMBER NOT NULL, CUST_ID NUMBER NOT NULL, TIME_ID DATE NOT NULL, CHANNEL_ID NUMBER NOT NULL, PROMO_ID NUMBER NOT NULL, QUANTITY_SOLD NUMBER(10,2) NOT NULL, AMOUNT_SOLD NUMBER(10,2) NOT NULL ) ILM ADD POLICY COMPRESS FOR ARCHIVE HIGH SEGMENT AFTER 6 MONTHS OF NO ACCESS; SQL> SELECT SUBSTR(policy_name,1,24) AS POLICY_NAME, policy_type, enabled 2 FROM USER_ILMPOLICIES; POLICY_NAME POLICY_TYPE ENABLED -------------------- -------------------------- -------------- P41 DATA MOVEMENT YES ALTER TABLE sales MODIFY PARTITION sales_1995 ILM ADD POLICY COMPRESS FOR ARCHIVE HIGH SEGMENT AFTER 6 MONTHS OF NO ACCESS; SELECT SUBSTR(policy_name,1,24) AS POLICY_NAME, policy_type, enabled FROM USER_ILMPOLICIES; POLICY_NAME POLICY_TYPE ENABLE ------------------------ ------------- ------ P1 DATA MOVEMENT YES P2 DATA MOVEMENT YES /* You can disable an ADO policy with the following */ ALTER TABLE sales_ado ILM DISABLE POLICY P1; /* You can delete an ADO policy with the following */ ALTER TABLE sales_ado ILM DELETE POLICY P1; /* You can disable all ADO policies with the following */ ALTER TABLE sales_ado ILM DISABLE_ALL; /* You can delete all ADO policies with the following */ ALTER TABLE sales_ado ILM DELETE_ALL; /* You can disable an ADO policy in a partition with the following */ ALTER TABLE sales MODIFY PARTITION sales_1995 ILM DISABLE POLICY P2; /* You can delete an ADO policy in a partition with the following */ ALTER TABLE sales MODIFY PARTITION sales_1995 ILM DELETE POLICY P2; ILM ???????: ?????ILM ADP????,???????: ?????? ???? activity tracking, ????2????????,???????????????????: SEGMENT-LEVEL???????????????????? ROW-LEVEL????????,??????? ????????: 1??????? SEGMENT-LEVEL activity tracking ALTER TABLE interval_sales ILM  ENABLE ACTIVITY TRACKING SEGMENT ACCESS ???????INTERVAL_SALES??segment level  activity tracking,?????????????????? 2? ??????????? ALTER TABLE emp ILM ENABLE ACTIVITY TRACKING (CREATE TIME , WRITE TIME); 3????????? ALTER TABLE emp ILM ENABLE ACTIVITY TRACKING  (READ TIME); ?12.1.0.1.0?????? ??HEAT_MAP??????????, ?????system??session?????heap_map????????????? ?????????HEAT MAP??,? ALTER SYSTEM SET HEAT_MAP = ON; ?HEAT MAP??????,??????????????????????????  ??SYSTEM?SYSAUX????????????? ???????HEAT MAP??: ALTER SYSTEM SET HEAT_MAP = OFF; ????? HEAT_MAP????, ?HEAT_MAP??? ?????????????????????? ?HEAT_MAP?????????Automatic Data Optimization (ADO)??? ??ADO??,Heat Map ?????????? ????V$HEAT_MAP_SEGMENT ??????? HEAT MAP?? SQL> select * from V$heat_map_segment; no rows selected SQL> alter session set heat_map=on; Session altered. SQL> select * from scott.emp; EMPNO ENAME JOB MGR HIREDATE SAL COMM DEPTNO ---------- ---------- --------- ---------- --------- ---------- ---------- ---------- 7369 SMITH CLERK 7902 17-DEC-80 800 20 7499 ALLEN SALESMAN 7698 20-FEB-81 1600 300 30 7521 WARD SALESMAN 7698 22-FEB-81 1250 500 30 7566 JONES MANAGER 7839 02-APR-81 2975 20 7654 MARTIN SALESMAN 7698 28-SEP-81 1250 1400 30 7698 BLAKE MANAGER 7839 01-MAY-81 2850 30 7782 CLARK MANAGER 7839 09-JUN-81 2450 10 7788 SCOTT ANALYST 7566 19-APR-87 3000 20 7839 KING PRESIDENT 17-NOV-81 5000 10 7844 TURNER SALESMAN 7698 08-SEP-81 1500 0 30 7876 ADAMS CLERK 7788 23-MAY-87 1100 20 7900 JAMES CLERK 7698 03-DEC-81 950 30 7902 FORD ANALYST 7566 03-DEC-81 3000 20 7934 MILLER CLERK 7782 23-JAN-82 1300 10 14 rows selected. SQL> select * from v$heat_map_segment; OBJECT_NAME SUBOBJECT_NAME OBJ# DATAOBJ# TRACK_TIM SEG SEG FUL LOO CON_ID -------------------- -------------------- ---------- ---------- --------- --- --- --- --- ---------- EMP 92997 92997 23-JUL-13 NO NO YES NO 0 ??v$heat_map_segment???,?v$heat_map_segment??????????????X$HEATMAPSEGMENT V$HEAT_MAP_SEGMENT displays real-time segment access information. Column Datatype Description OBJECT_NAME VARCHAR2(128) Name of the object SUBOBJECT_NAME VARCHAR2(128) Name of the subobject OBJ# NUMBER Object number DATAOBJ# NUMBER Data object number TRACK_TIME DATE Timestamp of current activity tracking SEGMENT_WRITE VARCHAR2(3) Indicates whether the segment has write access: (YES or NO) SEGMENT_READ VARCHAR2(3) Indicates whether the segment has read access: (YES or NO) FULL_SCAN VARCHAR2(3) Indicates whether the segment has full table scan: (YES or NO) LOOKUP_SCAN VARCHAR2(3) Indicates whether the segment has lookup scan: (YES or NO) CON_ID NUMBER The ID of the container to which the data pertains. Possible values include:   0: This value is used for rows containing data that pertain to the entire CDB. This value is also used for rows in non-CDBs. 1: This value is used for rows containing data that pertain to only the root n: Where n is the applicable container ID for the rows containing data The Heat Map feature is not supported in CDBs in Oracle Database 12c, so the value in this column can be ignored. ??HEAP MAP??????????????????,????DBA_HEAT_MAP_SEGMENT???????? ???????HEAT_MAP_STAT$?????? ??Automatic Data Optimization??????: ????1: SQL> alter system set heat_map=on; ?????? ????????????? scott?? http://www.askmaclean.com/archives/scott-schema-script.html SQL> grant all on dbms_lock to scott; ????? SQL> grant dba to scott; ????? @ilm_setup_basic C:\APP\XIANGBLI\ORADATA\MACLEAN\ilm.dbf @tktgilm_demo_env_setup SQL> connect scott/tiger ; ???? SQL> select count(*) from scott.employee; COUNT(*) ---------- 3072 ??? 1 ?? SQL> set serveroutput on SQL> exec print_compression_stats('SCOTT','EMPLOYEE'); Compression Stats ------------------ Uncmpressed : 3072 Adv/basic compressed : 0 Others : 0 PL/SQL ???????? ???????3072?????? ????????? ????policy ???????????? alter table employee ilm add policy row store compress advanced row after 3 days of no modification / SQL> set serveroutput on SQL> execute list_ilm_policies; -------------------------------------------------- Policies defined for SCOTT -------------------------------------------------- Object Name------ : EMPLOYEE Subobject Name--- : Object Type------ : TABLE Inherited from--- : POLICY NOT INHERITED Policy Name------ : P1 Action Type------ : COMPRESSION Scope------------ : ROW Compression level : ADVANCED Tier Tablespace-- : Condition type--- : LAST MODIFICATION TIME Condition days--- : 3 Enabled---------- : YES -------------------------------------------------- PL/SQL ???????? SQL> select sysdate from dual; SYSDATE -------------- 29-7? -13 SQL> execute set_back_chktime(get_policy_name('EMPLOYEE',null,'COMPRESSION','ROW','ADVANCED',3,null,null),'EMPLOYEE',null,6); Object check time reset ... -------------------------------------- Object Name : EMPLOYEE Object Number : 93123 D.Object Numbr : 93123 Policy Number : 1 Object chktime : 23-7? -13 08.13.42.000000 ?? Distnt chktime : 0 -------------------------------------- PL/SQL ???????? ?policy?chktime???6??, ????set_back_chktime???????????????“????”?,?????????,???????? ?????? alter system flush buffer_cache; alter system flush buffer_cache; alter system flush shared_pool; alter system flush shared_pool; SQL> execute set_window('MONDAY_WINDOW','OPEN'); Set Maint. Window OPEN ----------------------------- Window Name : MONDAY_WINDOW Enabled? : TRUE Active? : TRUE ----------------------------- PL/SQL ???????? SQL> exec dbms_lock.sleep(60) ; PL/SQL ???????? SQL> exec print_compression_stats('SCOTT', 'EMPLOYEE'); Compression Stats ------------------ Uncmpressed : 338 Adv/basic compressed : 2734 Others : 0 PL/SQL ???????? ??????????????? Adv/basic compressed : 2734 ??????? SQL> col object_name for a20 SQL> select object_id,object_name from dba_objects where object_name='EMPLOYEE'; OBJECT_ID OBJECT_NAME ---------- -------------------- 93123 EMPLOYEE SQL> execute list_ilm_policy_executions ; -------------------------------------------------- Policies execution details for SCOTT -------------------------------------------------- Policy Name------ : P22 Job Name--------- : ILMJOB48 Start time------- : 29-7? -13 08.37.45.061000 ?? End time--------- : 29-7? -13 08.37.48.629000 ?? ----------------- Object Name------ : EMPLOYEE Sub_obj Name----- : Obj Type--------- : TABLE ----------------- Exec-state------- : SELECTED FOR EXECUTION Job state-------- : COMPLETED SUCCESSFULLY Exec comments---- : Results comments- : --- -------------------------------------------------- PL/SQL ???????? ILMJOB48?????policy?JOB,?12.1.0.1??J00x???? ?MMON_SLAVE???M00x???15????????? select sample_time,program,module,action from v$active_session_history where action ='KDILM background EXEcution' order by sample_time; 29-7? -13 08.16.38.369000000 ?? ORACLE.EXE (M000) MMON_SLAVE KDILM background EXEcution 29-7? -13 08.17.38.388000000 ?? ORACLE.EXE (M000) MMON_SLAVE KDILM background EXEcution 29-7? -13 08.17.39.390000000 ?? ORACLE.EXE (M000) MMON_SLAVE KDILM background EXEcution 29-7? -13 08.23.38.681000000 ?? ORACLE.EXE (M002) MMON_SLAVE KDILM background EXEcution 29-7? -13 08.32.38.968000000 ?? ORACLE.EXE (M000) MMON_SLAVE KDILM background EXEcution 29-7? -13 08.33.39.993000000 ?? ORACLE.EXE (M003) MMON_SLAVE KDILM background EXEcution 29-7? -13 08.33.40.993000000 ?? ORACLE.EXE (M003) MMON_SLAVE KDILM background EXEcution 29-7? -13 08.36.40.066000000 ?? ORACLE.EXE (M000) MMON_SLAVE KDILM background EXEcution 29-7? -13 08.37.42.258000000 ?? ORACLE.EXE (M000) MMON_SLAVE KDILM background EXEcution 29-7? -13 08.37.43.258000000 ?? ORACLE.EXE (M000) MMON_SLAVE KDILM background EXEcution 29-7? -13 08.37.44.258000000 ?? ORACLE.EXE (M000) MMON_SLAVE KDILM background EXEcution 29-7? -13 08.38.42.386000000 ?? ORACLE.EXE (M001) MMON_SLAVE KDILM background EXEcution select distinct action from v$active_session_history where action like 'KDILM%' KDILM background CLeaNup KDILM background EXEcution SQL> execute set_window('MONDAY_WINDOW','CLOSE'); Set Maint. Window CLOSE ----------------------------- Window Name : MONDAY_WINDOW Enabled? : TRUE Active? : FALSE ----------------------------- PL/SQL ???????? SQL> drop table employee purge ; ????? ???? ????? spool ilm_usecase_1_cleanup.lst @ilm_demo_cleanup ; spool off

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• Solving embarassingly parallel problems using Python multiprocessing

  - by gotgenes

  How does one use multiprocessing to tackle embarrassingly parallel problems? Embarassingly parallel problems typically consist of three basic parts: Read input data (from a file, database, tcp connection, etc.). Run calculations on the input data, where each calculation is independent of any other calculation. Write results of calculations (to a file, database, tcp connection, etc.). We can parallelize the program in two dimensions: Part 2 can run on multiple cores, since each calculation is independent; order of processing doesn't matter. Each part can run independently. Part 1 can place data on an input queue, part 2 can pull data off the input queue and put results onto an output queue, and part 3 can pull results off the output queue and write them out. This seems a most basic pattern in concurrent programming, but I am still lost in trying to solve it, so let's write a canonical example to illustrate how this is done using multiprocessing. Here is the example problem: Given a CSV file with rows of integers as input, compute their sums. Separate the problem into three parts, which can all run in parallel: Process the input file into raw data (lists/iterables of integers) Calculate the sums of the data, in parallel Output the sums Below is traditional, single-process bound Python program which solves these three tasks: #!/usr/bin/env python # -*- coding: UTF-8 -*- # basicsums.py """A program that reads integer values from a CSV file and writes out their sums to another CSV file. """ import csv import optparse import sys def make_cli_parser(): """Make the command line interface parser.""" usage = "\n\n".join(["python %prog INPUT_CSV OUTPUT_CSV", __doc__, """ ARGUMENTS: INPUT_CSV: an input CSV file with rows of numbers OUTPUT_CSV: an output file that will contain the sums\ """]) cli_parser = optparse.OptionParser(usage) return cli_parser def parse_input_csv(csvfile): """Parses the input CSV and yields tuples with the index of the row as the first element, and the integers of the row as the second element. The index is zero-index based. :Parameters: - `csvfile`: a `csv.reader` instance """ for i, row in enumerate(csvfile): row = [int(entry) for entry in row] yield i, row def sum_rows(rows): """Yields a tuple with the index of each input list of integers as the first element, and the sum of the list of integers as the second element. The index is zero-index based. :Parameters: - `rows`: an iterable of tuples, with the index of the original row as the first element, and a list of integers as the second element """ for i, row in rows: yield i, sum(row) def write_results(csvfile, results): """Writes a series of results to an outfile, where the first column is the index of the original row of data, and the second column is the result of the calculation. The index is zero-index based. :Parameters: - `csvfile`: a `csv.writer` instance to which to write results - `results`: an iterable of tuples, with the index (zero-based) of the original row as the first element, and the calculated result from that row as the second element """ for result_row in results: csvfile.writerow(result_row) def main(argv): cli_parser = make_cli_parser() opts, args = cli_parser.parse_args(argv) if len(args) != 2: cli_parser.error("Please provide an input file and output file.") infile = open(args[0]) in_csvfile = csv.reader(infile) outfile = open(args[1], 'w') out_csvfile = csv.writer(outfile) # gets an iterable of rows that's not yet evaluated input_rows = parse_input_csv(in_csvfile) # sends the rows iterable to sum_rows() for results iterable, but # still not evaluated result_rows = sum_rows(input_rows) # finally evaluation takes place as a chain in write_results() write_results(out_csvfile, result_rows) infile.close() outfile.close() if __name__ == '__main__': main(sys.argv[1:]) Let's take this program and rewrite it to use multiprocessing to parallelize the three parts outlined above. Below is a skeleton of this new, parallelized program, that needs to be fleshed out to address the parts in the comments: #!/usr/bin/env python # -*- coding: UTF-8 -*- # multiproc_sums.py """A program that reads integer values from a CSV file and writes out their sums to another CSV file, using multiple processes if desired. """ import csv import multiprocessing import optparse import sys NUM_PROCS = multiprocessing.cpu_count() def make_cli_parser(): """Make the command line interface parser.""" usage = "\n\n".join(["python %prog INPUT_CSV OUTPUT_CSV", __doc__, """ ARGUMENTS: INPUT_CSV: an input CSV file with rows of numbers OUTPUT_CSV: an output file that will contain the sums\ """]) cli_parser = optparse.OptionParser(usage) cli_parser.add_option('-n', '--numprocs', type='int', default=NUM_PROCS, help="Number of processes to launch [DEFAULT: %default]") return cli_parser def main(argv): cli_parser = make_cli_parser() opts, args = cli_parser.parse_args(argv) if len(args) != 2: cli_parser.error("Please provide an input file and output file.") infile = open(args[0]) in_csvfile = csv.reader(infile) outfile = open(args[1], 'w') out_csvfile = csv.writer(outfile) # Parse the input file and add the parsed data to a queue for # processing, possibly chunking to decrease communication between # processes. # Process the parsed data as soon as any (chunks) appear on the # queue, using as many processes as allotted by the user # (opts.numprocs); place results on a queue for output. # # Terminate processes when the parser stops putting data in the # input queue. # Write the results to disk as soon as they appear on the output # queue. # Ensure all child processes have terminated. # Clean up files. infile.close() outfile.close() if __name__ == '__main__': main(sys.argv[1:]) These pieces of code, as well as another piece of code that can generate example CSV files for testing purposes, can be found on github. I would appreciate any insight here as to how you concurrency gurus would approach this problem. Here are some questions I had when thinking about this problem. Bonus points for addressing any/all: Should I have child processes for reading in the data and placing it into the queue, or can the main process do this without blocking until all input is read? Likewise, should I have a child process for writing the results out from the processed queue, or can the main process do this without having to wait for all the results? Should I use a processes pool for the sum operations? If yes, what method do I call on the pool to get it to start processing the results coming into the input queue, without blocking the input and output processes, too? apply_async()? map_async()? imap()? imap_unordered()? Suppose we didn't need to siphon off the input and output queues as data entered them, but could wait until all input was parsed and all results were calculated (e.g., because we know all the input and output will fit in system memory). Should we change the algorithm in any way (e.g., not run any processes concurrently with I/O)?

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• Saving filtered results from an Excel workbook to a CSV file

  - by Niklas Winde

  I have an Excel workbook with a lot of rows in it. I filter it using the values of one column and then I want to save the filtered results to a CSV file. When I do "Save as..." I get all the rows. I can copy paste the filtered results to another sheet and save from there but I'd rather not. It's Excel 2003 primarily.

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• Split (parts of) image into several smaller (same size) pieces non-manually

  - by hlovdal

  If I have an image with a table containing several rows, say like the periodic table: Are there any tool I can use to split this into one smaller image with the H He row, another image for the Li Be ... Ne row, etc? The tool does not have to detect the row borders by itself, specifying a start offset + row height in pixels is ok. Manually selecting and cutting/copying in gimp is not an option, I have way to many rows to process.

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• Get results by name in Excel 2010

  - by Tom

  I need to parse through the data below and show results like: Mary notready=483 training=452 break=30 I have the formulas — what I'm having trouble with is: The names are first, then 7 to 10 rows of data and what I need is some kind of array that will pull 1st Break_100 under that name, even though they are in different rows. Mary Summary: 08:02:32 () 9/19/2012 Not_Ready_Default_Reason_Code 00:00:05 Training_3000 07:32:21 Break_1000 00:30:06 daily 9/19/2012 08:02:32 Agent: 08:02:32 Dan Summary: 01:18:33 () 9/19/2012 Break_1000 00:34:27 Not_Ready_Default_Reason_Code 00:01:37 Personal_4000 00:42:29 daily 9/19/2012 01:18:33 Agent: 01:18:33

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• Show only row that follow criteria in Excel

  - by user10826

  Hi, in Excel, how can one filter and just show on the WORKSHEET rows that follow some criteria, for instance, rows that have the value "1" in the second column? In case it can be done, can I add this action somehow to a button on the toolbar? I use Excel for Mac 2008 Thanks

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• django modelformset - one form per related table row

  - by Toby

  Hello, I have two models: class Model1(): name = CharField() url = CharField() class Model2(): model1 = ForeignKey(Model1) user = ForeignKey(User) zzz = CharField() There are 5 rows for model1 in the database, these are fixed and will rarely change. I need to display a formset for model2 that allows users to enter the zzz value, the formset must always show one form per row in the model1 table, the label for each form in the formset must be the name of the related model1. If the user deletes a model2 in the formset the next time the page loads it will render an empty zzz value for that form and the user must be able to edit the previous zzz value - meaning it must be pre populated with all model2 rows associated with the user. The idea is to print each row in the model1 table as a form instead of the user selecting the related model1 name in a select box. I know its not that complicated, but I'm seriously stumped and keep going round in circles!! Many thanks in advance. Similar to http://stackoverflow.com/questions/298779/form-or-formset-to-handle-multiple-table-rows-in-django

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• MySQL Query Select using sub-select takes too long

  - by True Soft

  I noticed something strange while executing a select from 2 tables: SELECT * FROM table_1 WHERE id IN ( SELECT id_element FROM table_2 WHERE column_2=3103); This query took approximatively 242 seconds. But when I executed the subquery SELECT id_element FROM table_2 WHERE column_2=3103 it took less than 0.002s (and resulted 2 rows). Then, when I did SELECT * FROM table_1 WHERE id IN (/* prev.result */) it was the same: 0.002s. I was wondering why MySQL is doing the first query like that, taking much more time than the last 2 queries separately? Is it an optimal solution for selecting something based from the results of a sub-query? Other details: table_1 has approx. 9000 rows, and table_2 has 90000 rows. After I added an index on column_2 from table_2, the first query took 0.15s.

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• SQLPlus - spooling to multiple files from PL/SQL blocks

  - by FrustratedWithFormsDesigner

  I have a query that returns a lot of data into a CSV file. So much, in fact, that Excel can't open it - there are too many rows. Is there a way to control spool to spool to a new file everytime 65000 rows have been processed? Ideally, I'd like to have my output in files named in sequence, such as large_data_1.csv, large_data_2.csv, large_data_3.csv, etc... I could use dbms_output in a PL/SQL block to control how many rows are output, but then how would I switch files, as spool does not seem to be accessible from PL/SQL blocks? (Oracle 10g)

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• PowerShell dataGridView - Copy only one Row into an other dataGridView

  - by Marcel L.

  I´ve got a very short question about the "dataGridView". I´m developing with the Microsoft PowerShell and I want to copy one Row (from $dataGridView1) to the other ($dataGridView2). With this Code I can only Copy the Value of the last focused Cell. I´ve tried to make this for a whole Row, but it´s only working with Cells. Here is my Code: **$btnListeAdd.Add_Click({ $Row = $dataGridView1.Rows[ $dataGridView1.CurrentCell.RowIndex ] $dataGridView2.Rows.Add( $dataGridView1.CurrentCell.Value ) $dataGridView1.Rows.Remove( $Row ) }) $tabListe.Controls.Add($btnListeAdd)** Only the market Cell in $dataGridView1 (similar Column 1 or 2) will be cloned in Column1 in $dataGridView2 - in a extra Row, yey. Thanks for helping me. Please show mercy. It´s my first day with the PowerShell. Kind regards, Marcel L.

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• Question with R. Element wise multiplication, addition, and division with 2 data.frames with varying

  - by Michael

  I have a various data.frames with columns of the same length where I am trying to multiple 2 rows together element-wise and then sum this up. For example, below are two vectors I would like to perform this operation with. > a.1[186,] q01_a q01_b q01_c q01_d q01_e q01_f q01_g q01_h q01_i q01_j q01_k q01_l q01_m 3 3 3 3 2 2 2 3 1 NA NA 2 2 and > u.1[186,] q04_avl_a q04_avl_b q04_avl_c q04_avl_d q04_avl_e q04_avl_f q04_avl_g q04_avl_h q04_avl_i q04_avl_j q04_avl_k q04_avl_l q04_avl_m 4 2 3 4 3 4 4 4 3 4 3 3 3` The issue is that various rows have varying numbers of NA's. What I would like to do is skip the multiplication with any missing values ( the 10th and 11th position from my above example), and then after the addition divide by the number of elements that were multiplied (11 from the above example). Most rows are complete and would just be multiplied by 13. Thank you!

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• java cosine similarity problem

  - by agazerboy

  Hi again :) I developed some java program to calculate cosine similarity on the basis of TF*IDF. It worked very well. But there is one problem.... :( for example: If I have following two matrix and I want to calculate cosine similarity it does not work as rows are not same in length doc 1 1 2 3 4 5 6 doc 2 1 2 3 4 5 6 7 8 5 2 4 9 if rows and colums are same in length then my program works very well but it does not if rows and columns are not in same length. Any tips ???

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• Session state in asp.net mvc

  - by tiff

  I would like to know how to use session state in a simple log in log out in asp.net mvc.. I have a code here in my controller that I've retrieved from my mysql database for my session log in..but I don't really know how to manipulate it.. <AcceptVerbs(HttpVerbs.Post)> _ Function Index(ByVal username As String, ByVal password As String, ByVal department As String) As ActionResult Dim user As DataTable user = Account.userSelect(username:=username, password:=password, department:=department) If user.Rows.Count = 0 Then Return RedirectToAction("Index", "Home") Else Session("username") = user.Rows(0).Item("username") Session("department") = user.Rows(0).Item("department") Return RedirectToAction("News", "Administration") End If End Function Thank you!

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• Filtering MySQL query result according to a interval of timestamp

  - by celalo

  Let's say I have a very large MySQL table with a timestamp field. So I want to filter out some of the results not to have too many rows because I am going to print them. Let's say the timestamps are increasing as the number of rows increase and they are like every one minute on average. (Does not necessarily to be exactly once every minute, ex: 2010-06-07 03:55:14, 2010-06-07 03:56:23, 2010-06-07 03:57:01, 2010-06-07 03:57:51, 2010-06-07 03:59:21 ...) As I mentioned earlier I want to filter out some of the records, I do not have specific rule to do that, but I was thinking to filter out the rows according to the timestamp interval. After I achieve filtering I want to have a result set which has a certain amount of minutes between timestamps on average (ex: 2010-06-07 03:20:14, 2010-06-07 03:29:23, 2010-06-07 03:38:01, 2010-06-07 03:49:51, 2010-06-07 03:59:21 ...) Last but not least, the operation should not take incredible amount of time, I need this functionality to be almost fast as a normal select operation. Do you have any suggestions?

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• How to split string in group in vb.net

  - by amol kadam

  Hi. i'm amol kadam,I want to know how to split string in two part.My string is in Time format (12:12).& I want to seperate this in hour & minute format.the datatype for all variables are string. for hour variable used strTimeHr & for minute strTimeMin .I tried below code but their was a exception "Index and length must refer to a location within the string. Parameter name: length" If Not (objDS.Tables(0).Rows(0)("TimeOfAccident") Is Nothing Or objDS.Tables(0).Rows(0)("TimeOfAccident") Is System.DBNull.Value) Then strTime = objDS.Tables(0).Rows(0)("TimeOfAccident") 'strTime taking value 12:12 index = strTime.IndexOf(":") 'index taking value 2 lastIndex = strTime.Length 'Lastindex taking value 5 strTimeHr = strTime.Substring(0, index) 'strTime taking value 12 correctly strTimeMin = strTime.Substring(index + 1, lastIndex) 'BUT HERE IS PROBLEM OCCURE strTimeMin Doesn't taking any value Me.NumUpDwHr.Text = strTimeHr Me.NumUpDwMin.Text = strTimeMin End If

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• How to "interleave" two DataTables.

  - by Brent

  Take these two lists: List 1 Red Green Blue List 2 Brown Red Blue Purple Orange I'm looking for a way to combine these lists together to produce: List 3 Brown Red Green Blue Purple Orange I think the basic rules are these: 1) Insert on top the list any row falling before the first common row (e.g., Brown comes before the first common row, Red); 2) Insert items between rows if both lists have two items (e.g., List 1 inserts Green between Red and Blue); and 3) Insert rows on the bottom if the there's no "between-ness" found in 2 (e.g., List 2 inserts Orange at the bottom). The lists are stored in a DataTable. I'm guessing I'll have to switch between them while iterating, but I'm having a hard time figuring out a method of combining the rows. Thanks for any help. --Brent

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• Hiding Row in DataGridView Very Slow

  - by Ed Schwehm

  I have a DataGridView in a Winforms app that has about 1000 rows (unbound) and 50 columns. Hiding a column takes a full 2 seconds. When I want to hide about half the rows, this becomes a problem. private void ShowRows(string match) { this.SuspendLayout(); foreach (DataGridViewRow row in uxMainList.Rows) { if (match == row.Cells["thisColumn"].Value.ToString())) { row.Visible = false; } else { row.Visible = true; } } this.ResumeLayout(); } I did some testing by adding by addingConsole.WriteLine(DateTime.Now)around the actions, androw.Visible = falseis definitely the slow bit. Am I missing something obvious, like setting IsReallySlow = false? Or do I have to go ahead and enable Virtual Mode and code up the necessary events?

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• Add columns to a datatable in c#?

  - by Pandiya Chendur

  I have a csv reader class that reads a .csv file and its values.... I have created datatable out of it... Consider my Datatable contains three header columns Name,EmailId,PhoneNo.... The values have been added successfully.... Now i want to add two columns IsDeleted,CreatedDate to this datatable... I have tried this but it doesn't seem to work, foreach (string strHeader in headers) { dt.Columns.Add(strHeader); } string[] data; while ((data = reader.GetCSVLine()) != null) { dt.Rows.Add(data); } dt.Columns.Add("IsDeleted", typeof(byte)); dt.Columns.Add(new DataColumn("CreatedDate", typeof(DateTime))); foreach (DataRow dr in dt.Rows) { dr["IsDeleted"] = Convert.ToByte(0); dr["CreatedDate"] = Convert.ToDateTime(System.DateTime.Now.ToString()); dt.Rows.Add(dr); } When i try to add isdeleted values an error saying This row already belongs to this table. ....

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• SQLite - a smart way to remove and add new objects

  - by Ilya

  Hi, I have a table in my database and I want for each row in my table to have an unique id and to have the rows named sequently. For example: I have 10 rows, each has an id - starting from 0, ending at 9. When I remove a row from a table, lets say - row number 5, there occurs a "hole". And afterwards I add more data, but the "hole" is still there. It is important for me to know exact number of rows and to have at every row data in order to access my table arbitrarily. There is a way in sqlite to do it? Or do I have to manually manage removing and adding of data? Thank you in advance, Ilya.

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• C# & Adding Dynamic META Tags

  - by Bry4n

  I have this code protected void Page_Load(object sender, EventArgs e) { DataSet.DestinationsDataTable GetDestinations = (DataSet.DestinationsDataTable)dta.GetData(); Page.Title = GetDestinations.Rows[0]["Meta_Title"].ToString(); HtmlMeta hm = new HtmlMeta(); HtmlHead head = (HtmlHead)Page.Header; hm.Name = GetDestinations.Rows[0]["Meta_Desc"].ToString(); hm.Content = GetDestinations.Rows[0]["Meta_Key"].ToString(); head.Controls.Add(hm); } And it's returning this error (on a content page) The Controls collection cannot be modified because the control contains code blocks (i.e. <% ... %>). Thoughts?

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• Paging enormous tables on DB2

  - by grenade

  We have a view that, without constraints, will return 90 million rows and a reporting application that needs to display paged datasets of that view. We're using nhibernate and recently noticed that its paging mechanism looks like this: select * from (select rownumber() over() as rownum, this_.COL1 as COL1_20_0_, this_.COL2 as COL2_20_0_ FROM SomeSchema.SomeView this_ WHERE this_.COL1 = 'SomeValue') as tempresult where rownum between 10 and 20 The query brings the db server to its knees. I think what's happening is that the nested query is assigning a row number to every row satisfied by the where clause before selecting the subset (rows 10 - 20). Since the nested query will return a lot of rows, the mechanism is not very efficient. I've seen lots of tips and tricks for doing this efficiently on other SQL platforms but I'm struggling to find a DB2 solution. In fact an article on IBM's own site recommends the approach that nhibernate has taken. Is there a better way?

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