SQL Server Script to Rebuild/Reorganize Fragmented Indexes When on a database’s table frequently running INSERT, UPDATE or DELETE queries than we can see indexes on the particular table gets fragmented and the SQL query may run slower as they may choose the non-optimal execution plan. Most of the people asking about Does SQL Server rebuild index automatically or any rebuild criteria? But Rebuilding/Reorganize of fragmented Indexes not supported automatically because rebuilding the indexes is expansive operation so be careful to schedule rebuilding via SQL Server Agent. But hare we are adopting an approach to rebuild or Reorganize only the necessary Indexes instead of all index rebuild, As a general recommendation, the index needs to rebuild that gets fragment percentage more than 30% and reorganize the index that has fragment percentage greater than 10% and less than 30%. The below script rebuilding index one by one, so it won’t be an expansive operation on the production database. --- Rebuild/Reorganize Indexes CREATE TABLE #IndexRebuild ( DatabaseName SYSNAME, SchemaName SYSNAME, TableName SYSNAME, IndexName SYSNAME, [Fragmentation%] FLOAT ) INSERT INTO #IndexRebuild SELECT DB_NAME(DB_ID()) AS DatabaseName, ss.name AS SchemaName, OBJECT_NAME (s.object_id) AS TableName, i.name AS IndexName, s.avg_fragmentation_in_percent AS [Fragmentation%] FROM sys.dm_db_index_physical_stats(db_id(),NULL, NULL, NULL, 'SAMPLED') s INNER JOIN sys.indexes i ON s.[object_id] = i.[object_id] AND s.index_id = i.index_id INNER JOIN sys.objects o ON s.object_id = o.object_id INNER JOIN sys.schemas ss ON ss.[schema_id] = o.[schema_id] WHERE s.database_id = DB_ID() AND i.index_id != 0 AND s.record_count > 0 AND o.is_ms_shipped = 0 AND s.avg_fragmentation_in_percent > 10 DECLARE @RebuildSQL NVARCHAR(MAX) SET @RebuildSQL = '' SELECT @RebuildSQL = @RebuildSQL + CASE WHEN [Fragmentation%] > 30 THEN CHAR(10) + 'ALTER INDEX ' + QUOTENAME(IndexName) + ' ON ' + QUOTENAME(SchemaName) + '.' + QUOTENAME(TableName) + ' REBUILD;' WHEN [Fragmentation%] > 10 THEN CHAR(10) + 'ALTER INDEX ' + QUOTENAME(IndexName) + ' ON ' + QUOTENAME(SchemaName) + '.' + QUOTENAME(TableName) + ' REORGANIZE;' END FROM #IndexRebuild WHERE [Fragmentation%] > 10 DECLARE @StartOffset INT DECLARE @Length INT SET @StartOffset = 0 SET @Length = 4000 WHILE (@StartOffset < LEN(@RebuildSQL)) BEGIN PRINT SUBSTRING(@RebuildSQL, @StartOffset, @Length) SET @StartOffset = @StartOffset + @Length END PRINT SUBSTRING(@RebuildSQL, @StartOffset, @Length) EXECUTE sp_executesql @RebuildSQL DROP TABLE #IndexRebuild The scripts will work like a charm, You can create a stored procedure and can call the stored procedure via the SQL Server agent or via windows task scheduler.

check if values are between two values pandas

pradeepkumarjse

I have a two values that are being found in a for loop like so:

for i in range(df_zones.shape[0]):

   filter_max = df_labels[df_labels['Labels'] == i].sort_values(by='level').iloc[-1]
   filter_min = df_labels[df_labels['Labels'] == i].sort_values(by='level').iloc[0]

I have another dataframe with 4 columns of measurements with a timeseries index, like so:

DateTime meas1 meas2 meas3 meas4 2022-1-1 1.1 1.2 1.3 1.1

There are 1000's of rows of data.

What I am trying to do is have another column that is labeled as 'isZone', where this means, are any of the values in the row between filter_max and filter_min.

DateTime meas1 meas2 meas3 meas4 isZone 2022-1-1 1.1 1.5 1.5 1.7 0 2022-1-2 2.2 1.4 1.5 1.7 0 2022-1-3 3.1 1.2 1.3 1.1 1 2022-1-4 4.1 1.2 1.3 1.1 1 2022-1-5 5.1 1.2 1.3 1.1 1

I have read about the pandas between function. But I really can't figure out how to make this work. Is there a quicker way to do this in numpy? any guidance would be appreciated.