createLeftSemiJoinEngine(name, leftTable, rightTable, outputTable, metrics, matchingColumn, [garbageSize=5000], [updateRightTable=false])


Create a left semi join engine. For each record from the left table, the left semi join engine finds the matching records from the right table, and returns a table of its joining result. Unmatched records will not be returned.

If an incoming record has the identical matchingColumn of an existing record in the right table, only the first/latest record (determined by parameter updateRightTable) is kept.


Only one record with the indentical matchingColumn is kept by the engine in the right table, and data in the right table will not be removed from memory. Therefore, a large number of distinct values of matchingColumn should be avoided, otherwise an OOM problem may occur.

For more details of streaming engines, refer to Streaming Engines


name is a string indicating the name of the left semi join engine. It is the unique identifier of the engine on a data/compute node. It can contain letters, numbers and underscores and must start with a letter.

leftTable is a table object whose schema must be the same as the stream table to which the engine subscribes. It does not matter whether the table contains data or not.

rightTable is a table object whose schema must be the same as the stream table to which the engine subscribes. It does not matter whether the table contains data or not.

outputTable is a table object to hold the calculation results. Create an empty table and specify the column names and types before calling the function.

The columns of outputTable are in the following order:

(1) The first column(s) are the column(s) on which the tables are joined, arranged in the same order as specified in matchingColumn.

(2) Then followed by the calculation results of metrics. There can be one or multiple columns.

metrics is metacode (which can be a tuple) specifying the calculation formulas. For more information about metacode, please refer to Metaprogramming.

  • metrics can use one or more expressions, built-in or user-defined functions, but not aggregate functions.

  • metrics can be functions that return multiple values and the columns in the output table to hold the return values must be specified. For example, <func(price) as `col1`col2>.

  • To specify a column that exists in both the left and the right tables, use the format tableName.colName. By default, the column from the left table is used.

  • The column names specified in metrics are case-sensitive and must be consistent with the column names of the input tables.

matchingColumn is a STRING scaler/vector/tuple indicating the column(s) on which the tables are joined. It supports integral, temporal or literal (except UUID) types.

1. When there is only 1 column to match - If the names of the columns to match are the same in both tables, matchingColumn should be specified as a STRING scalar; otherwise it’s a tuple of two elements. For example, if the column is named “sym” in the left table and “sym1” in the right table, then matchingColumn = [[`sym],[`sym1]].

2. When there are multiple columns to match - If both tables share the names of all columns to match, matchingColumn is a STRING vector; otherwise it’s a tuple of two elements. For example, if the columns are named “timestamp” and “sym” in the left table, whereas in the right table they’re named “timestamp” and “sym1”, then matchingColumn = [[`timestamp, `sym], [`timestamp,`sym1]].

garbageSize (optional) is a positive integer. The default value is 5,000. Unlike other join engines, the garbageSize parameter for left semi join engine is only used to remove the historical data from the left table. The system will clear the data from the left table when the number of joined records exceeds garbageSize.

updateRightTable (optional) is a BOOLEAN value indicating whether to output the first record (updateRightTable = true) or the latest record (updateRightTable = false) when there are more than one matching records in the right table. The default value is false.


$ share streamTable(1:0, `time`sym`price, [TIMESTAMP, SYMBOL, DOUBLE]) as leftTable
$ share streamTable(1:0, `time`sym1`vol, [TIMESTAMP, SYMBOL, INT]) as rightTable

$ output=table(100:0, `time`sym`price`vol`total, [TIMESTAMP, SYMBOL, DOUBLE, INT, DOUBLE])
$ lsjEngine=createLeftSemiJoinEngine(name="test1", leftTable=leftTable, rightTable=rightTable, outputTable=output,  metrics=<[price, vol,price*vol]>, matchingColumn=[[`time,`sym], [`time,`sym1]], updateRightTable=true)

$ subscribeTable(tableName="leftTable", actionName="joinLeft", offset=0, handler=appendForJoin{lsjEngine, true}, msgAsTable=true)
$ subscribeTable(tableName="rightTable", actionName="joinRight", offset=0, handler=appendForJoin{lsjEngine, false}, msgAsTable=true)

$ v = [1, 5, 10, 15]
$ tp1=table(2012.01.01T00:00:00.000+v as time, take(`AAPL, 4) as sym, rand(100,4) as price)
$ leftTable.append!(tp1)

$ v = [1, 1, 3, 4, 5, 5, 5, 15]
$ tp2=table(2012.01.01T00:00:00.000+v as time, take(`AAPL, 8) as sym, rand(100,8) as vol)
$ rightTable.append!(tp2)

$ select * from output





















To execute the above script again, delete the engine and unsubscribe:

$ dropStreamEngine("test1")
$ lsjEngine=NULL
$ unsubscribeTable(tableName="leftTable", actionName="joinLeft")
$ unsubscribeTable(tableName="rightTable", actionName="joinRight")