wbo4958 commented on code in PR #48791:
URL: https://github.com/apache/spark/pull/48791#discussion_r1877882367
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sql/connect/server/src/main/scala/org/apache/spark/sql/connect/service/SessionHolder.scala:
##########
@@ -111,6 +112,9 @@ case class SessionHolder(userId: String, sessionId: String,
session: SparkSessio
private[spark] lazy val dataFrameCache: ConcurrentMap[String, DataFrame] =
new ConcurrentHashMap()
+ // ML model cache
+ private[connect] lazy val mlCache = new MLCache()
Review Comment:
Currently, I have no idea about the size of the objects, some object should
be small, while some are large, it depends.
Yes, the de-constructor of the python class will trigger a GRPC to delete
the cache on the server side.
##########
mllib/src/main/scala/org/apache/spark/ml/util/Summary.scala:
##########
@@ -0,0 +1,26 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one or more
+ * contributor license agreements. See the NOTICE file distributed with
+ * this work for additional information regarding copyright ownership.
+ * The ASF licenses this file to You under the Apache License, Version 2.0
+ * (the "License"); you may not use this file except in compliance with
+ * the License. You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+package org.apache.spark.ml.util
+
+import org.apache.spark.annotation.Since
+
+/**
+ * Trait for the Summary
+ */
+@Since("4.0.0")
+private[spark] trait Summary
Review Comment:
Make all the summaries extend from this Summary, so in connect, we can match
to this trait and decide if the object of the summary needs to be cached.
##########
sql/connect/server/src/main/scala/org/apache/spark/sql/connect/ml/MLCache.scala:
##########
@@ -0,0 +1,70 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one or more
+ * contributor license agreements. See the NOTICE file distributed with
+ * this work for additional information regarding copyright ownership.
+ * The ASF licenses this file to You under the Apache License, Version 2.0
+ * (the "License"); you may not use this file except in compliance with
+ * the License. You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+package org.apache.spark.sql.connect.ml
+
+import java.util.UUID
+import java.util.concurrent.ConcurrentHashMap
+
+import org.apache.spark.internal.Logging
+
+/**
+ * MLCache is for caching ML objects, typically for models and summaries
evaluated by a model.
+ */
+private[connect] class MLCache extends Logging {
+ private val cachedModel: ConcurrentHashMap[String, Object] =
+ new ConcurrentHashMap[String, Object]()
+
+ /**
+ * Cache an object into a map of MLCache, and return its key
+ * @param obj
+ * the object to be cached
+ * @return
+ * the key
+ */
+ def register(obj: Object): String = {
+ val objectId = UUID.randomUUID().toString.takeRight(12)
Review Comment:
Hmm, we could use the full UUID string instead of just taking the 12 chars
from right.
> An alternative would be to generate a predictable Id.
Could you show me how to do that?
##########
sql/connect/common/src/main/protobuf/spark/connect/ml_common.proto:
##########
@@ -0,0 +1,107 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one or more
+ * contributor license agreements. See the NOTICE file distributed with
+ * this work for additional information regarding copyright ownership.
+ * The ASF licenses this file to You under the Apache License, Version 2.0
+ * (the "License"); you may not use this file except in compliance with
+ * the License. You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+syntax = 'proto3';
+
+package spark.connect;
+
+import "spark/connect/expressions.proto";
+
+option java_multiple_files = true;
+option java_package = "org.apache.spark.connect.proto";
+
+// MlParams stores param settings for ML Estimator / Transformer / Evaluator
+message MlParams {
+ // User-supplied params
+ map<string, Param> params = 1;
+}
+
+// Represents the parameter type of the ML instance, or the returned value
+// of the attribute
+message Param {
+ oneof param_type {
+ Expression.Literal literal = 1;
+ Vector vector = 2;
+ Matrix matrix = 3;
+ }
+}
+
+// MLOperator represents the ML operators like (Estimator, Transformer or
Evaluator)
+message MlOperator {
+ // The qualified name of the ML operator.
+ string name = 1;
+ // Unique id of the ML operator
+ string uid = 2;
Review Comment:
No, the UID is the Identifiable for each ML operators.
##########
sql/connect/server/src/main/scala/org/apache/spark/sql/connect/ml/MLUtils.scala:
##########
@@ -0,0 +1,293 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one or more
+ * contributor license agreements. See the NOTICE file distributed with
+ * this work for additional information regarding copyright ownership.
+ * The ASF licenses this file to You under the Apache License, Version 2.0
+ * (the "License"); you may not use this file except in compliance with
+ * the License. You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+package org.apache.spark.sql.connect.ml
+
+import java.util.ServiceLoader
+
+import scala.collection.immutable.HashSet
+import scala.jdk.CollectionConverters.{IterableHasAsScala, MapHasAsScala}
+
+import org.apache.commons.lang3.reflect.MethodUtils.{invokeMethod,
invokeStaticMethod}
+
+import org.apache.spark.connect.proto
+import org.apache.spark.ml.{Estimator, Transformer}
+import org.apache.spark.ml.linalg.{Matrices, Matrix, Vector, Vectors}
+import org.apache.spark.ml.param.Params
+import org.apache.spark.ml.util.MLWritable
+import org.apache.spark.sql.{DataFrame, Dataset}
+import org.apache.spark.sql.connect.common.LiteralValueProtoConverter
+import org.apache.spark.sql.connect.planner.SparkConnectPlanner
+import org.apache.spark.sql.connect.service.SessionHolder
+import org.apache.spark.util.Utils
+
+private[ml] object MLUtils {
+
+ private lazy val estimators: Map[String, Class[_]] = {
Review Comment:
Sounds good. Done
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