kbendick commented on a change in pull request #3977:
URL: https://github.com/apache/iceberg/pull/3977#discussion_r796157999
##########
File path: core/src/main/java/org/apache/iceberg/io/PartitionedFanoutWriter.java
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@@ -19,19 +19,52 @@
package org.apache.iceberg.io;
+import com.github.benmanes.caffeine.cache.Cache;
+import com.github.benmanes.caffeine.cache.Caffeine;
import java.io.IOException;
+import java.io.UncheckedIOException;
import java.util.Map;
+import java.util.concurrent.ConcurrentMap;
+import java.util.concurrent.TimeUnit;
import org.apache.iceberg.FileFormat;
import org.apache.iceberg.PartitionKey;
import org.apache.iceberg.PartitionSpec;
-import org.apache.iceberg.relocated.com.google.common.collect.Maps;
+import org.apache.iceberg.TableProperties;
+import org.apache.iceberg.util.PropertyUtil;
+import org.apache.iceberg.util.Tasks;
public abstract class PartitionedFanoutWriter<T> extends BaseTaskWriter<T> {
- private final Map<PartitionKey, RollingFileWriter> writers =
Maps.newHashMap();
+ private Cache<PartitionKey, RollingFileWriter> writers;
protected PartitionedFanoutWriter(PartitionSpec spec, FileFormat format,
FileAppenderFactory<T> appenderFactory,
- OutputFileFactory fileFactory, FileIO io, long
targetFileSize) {
+ OutputFileFactory fileFactory, FileIO io,
+ long targetFileSize, Map<String, String> properties)
{
super(spec, format, appenderFactory, fileFactory, io, targetFileSize);
+ int writersCacheSize = PropertyUtil.propertyAsInt(
+ properties,
+ TableProperties.PARTITIONED_FANOUT_WRITERS_CACHE_SIZE,
+ TableProperties.PARTITIONED_FANOUT_WRITERS_CACHE_SIZE_DEFAULT);
+ long evictionTimeout = PropertyUtil.propertyAsLong(
+ properties,
+ TableProperties.PARTITIONED_FANOUT_WRITERS_CACHE_EVICT_MS,
+ TableProperties.PARTITIONED_FANOUT_WRITERS_CACHE_EVICT_MS_DEFAULT);
+ initWritersCache(writersCacheSize, evictionTimeout);
+ }
+
+ private synchronized void initWritersCache(int writersCacheSize, long
evictionTimeout) {
+ if (writers == null) {
+ writers = Caffeine.newBuilder()
+ .maximumSize(writersCacheSize)
+ .expireAfterAccess(evictionTimeout, TimeUnit.MILLISECONDS)
+ .removalListener((key, value, cause) -> {
Review comment:
This would instantiate a thread pool and evicted items would enter a
queue to go in there.
So I believe the removalListener would be run in a background thread
instantiated by Caffeine.
```
You may specify a removal listener for your cache to perform some operation
when an entry is removed,
via Caffeine.removalListener(RemovalListener).
These operations are executed asynchronously using an Executor, where the
default executor is
ForkJoinPool.commonPool() and can be overridden via
Caffeine.executor(Executor).
```
But I'll take a further look into the details, especially with mutating the
value this way. I also have concerns about `expireAfterAccess`, as the "access"
in question has to come from the cache. It's not any access to the underlying
value (for example if Spark is already using the file writer, any operations it
calls on it that don't go through the cache won't count towards resetting the
time since last acces).
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