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https://issues.apache.org/jira/browse/TINKERPOP-2679?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=17496327#comment-17496327
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ASF GitHub Bot commented on TINKERPOP-2679:
-------------------------------------------
tkolanko commented on a change in pull request #1539:
URL: https://github.com/apache/tinkerpop/pull/1539#discussion_r812367486
##########
File path: docs/src/reference/gremlin-variants.asciidoc
##########
@@ -1721,6 +1721,32 @@ IMPORTANT: The preferred method for setting a
per-request timeout for scripts is
with bytecode may try `g.with(EVALUATION_TIMEOUT, 500)` within a script.
Scripts with multiple traversals and multiple
timeouts will be interpreted as a sum of all timeouts identified in the script
for that request.
+
+==== Processing results as they are returned from the Gremlin server
+
+
+The Gremlin JavaScript driver maintains a WebSocket connection to the Gremlin
server and receives messages according to the `batchSize` parameter on the per
request settings or the `resultIterationBatchSize` value configured for the
Gremlin server. When submitting scripts the default behavior is to wait for the
entire result set to be returned from a query before allowing any processing on
the result set.
+
+The following examples assume that you have 100 vertices in your graph.
+
+[source,javascript]
+----
+const result = await client.submit("g.V()");
+console.log(result.toArray()); // 100 - all the vertices in your graph
+----
+
+When working with larger result sets it may be beneficial for memory
management to process each chunk of data as it is returned from the gremlin
server. The Gremlin JavaScript driver can accept an optional callback to run on
each chunk of data returned.
+
+[source,javascript]
+----
+
+await client.submit("g.V()", {}, { batchSize: 25 }, (data) => {
Review comment:
Some of the existing tests don't like the changes I made to reduce
duplicate code from the original submit and the new stream method. I'll back
out of those and leave the duplicated code for now; it's not that much. If we
want to have this fixed up for 3.5.3 I can take a crack at it this weekend.
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> Update JavaScript driver to support processing messages as a stream
> -------------------------------------------------------------------
>
> Key: TINKERPOP-2679
> URL: https://issues.apache.org/jira/browse/TINKERPOP-2679
> Project: TinkerPop
> Issue Type: Improvement
> Components: javascript
> Affects Versions: 3.5.1
> Reporter: Tom Kolanko
> Priority: Minor
>
> The JavaScript driver's
> [_handleMessage|https://github.com/apache/tinkerpop/blob/d4bd5cc5a228fc22442101ccb6a9751653900d32/gremlin-javascript/src/main/javascript/gremlin-javascript/lib/driver/connection.js#L249]
> receives messages from the gremlin server and stores each message in an
> object associated with the handler for the specific request. Currently, the
> driver waits until all the data is available from the gremlin server before
> allowing further processing of it.
> However, this can lead to cases where a lot of memory is required to hold
> onto the results before any processing can take place. If we had the abilty
> to process results as they come in from the gremlin server we could reduce
> memory in some cases
> If you are open to it I would like to submit a PR where {{submit}} can take
> an optional callback which is run on each set of data returned from the
> gremlin server, rather than waiting for the entire result set.
> The following examples assume that you have 100 vertices in your graph.
> current behaviour:
> {code:javascript}
> const result = await client.submit("g.V()")
> console.log(result.toArray()) // 100 - all the vertices in your graph
> {code}
> proposed addition
> {code:javascript}
> await client.submit("g.V()", {}, { batchSize: 25 }, (data) => {
> console.log(data.toArray().length) // 25 - this callback will be called 4
> times (100 / 25 = 4)
> })
> {code}
> If the optional callback is not provided then the default behaviour is
> unchanged
> I have the changes running locally and the overall performance is unchanged,
> queries run about the same as they used to, however, for some specific
> queries memory usage has dropped considerably.
> With the process-on-message strategy the memory usage will be related to how
> large the {{batchSize}} is rather than the final result set. Using the
> default of 64 and testing some specific cases we have I can get the memory to
> go from 1.2gb to 10mb.
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