[SPARK-51974][CONNECT][ML] Limit model size and per-session model cache size #50751
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Signed-off-by: Weichen Xu <[email protected]>
Signed-off-by: Weichen Xu <[email protected]>
Signed-off-by: Weichen Xu <[email protected]>
Signed-off-by: Weichen Xu <[email protected]>
WeichenXu123
changed the title
WeichenXu123
changed the title
Signed-off-by: Weichen Xu <[email protected]>
Signed-off-by: Weichen Xu <[email protected]>
Signed-off-by: Weichen Xu <[email protected]>
Signed-off-by: Weichen Xu <[email protected]>
Signed-off-by: Weichen Xu <[email protected]>
xi-db
reviewed
May 2, 2025
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| val CONNECT_SESSION_CONNECT_MODEL_MAX_SIZE = | ||
| buildConf("spark.connect.session.connectML.model.maxSize") | ||
| .doc("Maximum size of the SparkML model. The size is in bytes.") |
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nit: "the SparkML model" -> "a single SparkML model"
xi-db
reviewed
May 2, 2025
| @@ -61,6 +61,31 @@ private[connect] class MLCache(sessionHolder: SessionHolder) extends Logging { | |||
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| private[ml] val totalSizeBytes: AtomicLong = new AtomicLong(0) | |||
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| private[ml] val totalModelCacheSizeBytes: AtomicLong = new AtomicLong(0) | |||
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The "totalSizeBytes" above is tracking the total size in memory. Why do we need to use a different totalModelCacheSizeBytes?
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What changes were proposed in this pull request?
Limit model size and per-session model cache size.
Why are the changes needed?
Motivation: This is for ML cache management, to avoid huge ML cache affecting Spark driver availability.
Does this PR introduce any user-facing change?
No.
How was this patch tested?
UT.
Was this patch authored or co-authored using generative AI tooling?
No.