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Id
7278385
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2011-09-02T01:25:27.840
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2018-08-03T20:48:09.820
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2018-08-03T20:48:09.820
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7071333
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2
Score
1
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text
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I used the jdbc-odbc bridge in Java to do just this in the past, but performance through ODBC is not great. I would suggest looking at something like <a href="http://jtds.sourceforge.net/" rel="nofollow noreferrer">http://jtds.sourceforge.net/</a> which is a pure Java driver that you can drop into a simple Groovy script like the following: <pre><code>import groovy.sql.Sql sql = Sql.newInstance( 'jdbc:jtds:sqlserver://serverName/dbName-CLASS;domain=domainName', 'username', 'password', 'net.sourceforge.jtds.jdbc.Driver' ) sql.eachRow( 'select * from tableName' ) { println "$it.id -- ${it.firstName} --" // probably write to mysql connection here or write to file, compress, transfer, load } </code></pre> The following performance numbers give you a feel for how it might perform: <a href="http://jtds.sourceforge.net/benchTest.html" rel="nofollow noreferrer">http://jtds.sourceforge.net/benchTest.html</a> You may find some performance advantages to dumping data to a mysql dumpfile format and using mysql loaddata instead of writing row by row. MySQL has some significant performance improvements for large data sets if you load infile's and doing things like atomic table swaps. We use something like this to quickly load large datafiles into mysql from one system to another e.g. This is the fastest mechanism to load data into mysql. But real time row by row might be a simple loop to do in groovy + some table to keep track of what row had been moved. <pre><code>mysql> select * from table into outfile 'tablename.dat'; shell> myisamchk --keys-used=0 -rq '/data/mysql/schema_name/tablename' mysql> load data infile 'tablename.dat' into table tablename; shell> myisamchk -rq /data/mysql/schema_name/tablename mysql> flush tables; mysql> exit; shell> rm tablename.dat </code></pre>
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1. This table or related slice is empty.
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1. POSQL Server to MySQL data transfer
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1. PTAnswer
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1. USdjdanlib
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1. USTodd Ellermann
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1. POSQL Server to MySQL data transfer
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A row detail

Detail views are divided into sections. All the information in the data section comes from columns in the selected row. The other sections display data from other, related rows.

Related data can be related in a to-one or a to-many fashion. Captions of data related in a to-many fashion link to a list view showing a filtered view of the table.

Try moving around until you find a non-empty to-many entry and click on the label to get to one. You can move back to the root by clicking on the database name in the header.