Release 0.8.5

README.md

@@ -52,6 +52,7 @@ and [filodb-discuss](https://groups.google.com/forum/#!forum/filodb-discuss) goo
 - [Code Walkthrough](#code-walkthrough)
 - [Building and Testing](#building-and-testing)
   - [Debugging serialization and queries](#debugging-serialization-and-queries)
+  - [Other debugging tips](#other-debugging-tips)
   - [Benchmarking](#benchmarking)
 - [You can help!](#you-can-help)
 
@@ -708,6 +709,13 @@ To dynamically change the log level, you can use the `/admin/loglevel` HTTP API
 
     curl -d 'trace' http://localhost:8080/admin/loglevel/com.esotericsoftware.minlog
 
+### Other debugging tips
+
+To debug raw record ingestion and data mismatches:
+
+* Set the `trace-filters` source config setting... see `timeseries-dev-source.conf` and `TimeSeriesShard` `tracedPartFilters`.  This will log every sample for time series matching criteria set in trace-filters.
+* Use the filtering capability in `filodb.kafka.TestConsumer` to print out raw records received from Kafka.
+
 ### Benchmarking
 
 To run benchmarks, from within SBT:

cassandra/src/main/scala/filodb.cassandra/columnstore/PartitionIndexTable.scala

@@ -6,7 +6,7 @@ import java.nio.ByteBuffer
 import scala.collection.JavaConverters._
 import scala.concurrent.{ExecutionContext, Future}
 
-import com.datastax.driver.core.ConsistencyLevel
+import com.datastax.driver.core.{ConsistencyLevel, SimpleStatement}
 import monix.reactive.Observable
 
 import filodb.cassandra.FiloCassandraConnector
@@ -40,17 +40,18 @@ sealed class PartitionIndexTable(val dataset: DatasetRef,
        |) WITH compression = {
                     'sstable_compression': '$sstableCompression'}""".stripMargin
 
-  lazy val readCql = session.prepare(s"SELECT segmentid, segment " +
-    s"FROM $tableString WHERE shard = ? AND timebucket = ? order by segmentid asc")
+  lazy val readCql = s"SELECT segmentid, segment " +
+    s"FROM $tableString WHERE shard = ? AND timebucket = ? order by segmentid asc"
 
   lazy val writePartitionCql = session.prepare(
     s"INSERT INTO $tableString (shard, timebucket, segmentid, segment) VALUES (?, ?, ?, ?) USING TTL ?")
     .setConsistencyLevel(writeConsistencyLevel)
 
   def getPartKeySegments(shard: Int, timeBucket: Int): Observable[PartKeyTimeBucketSegment] = {
-    val it = session.execute(readCql.bind(shard: JInt, timeBucket: JInt))
+    // fetch size should be low since each row is about an MB. Default fetchSize can result in ReadTimeouts at server
+    val it = session.execute(new SimpleStatement(readCql, shard: JInt, timeBucket: JInt).setFetchSize(15))
       .asScala.toIterator.map(row => {
-      PartKeyTimeBucketSegment(row.getInt("segmentid"),  row.getBytes("segment"))
+      PartKeyTimeBucketSegment(row.getInt("segmentid"), row.getBytes("segment"))
     })
     Observable.fromIterator(it)
   }

cassandra/src/main/scala/filodb.cassandra/metastore/CassandraMetaStore.scala

@@ -59,12 +59,12 @@ class CassandraMetaStore(config: Config, filoSessionProvider: Option[FiloSession
     checkpointTable.writeCheckpoint(dataset, shardNum, groupNum, offset)
   }
 
-  def readCheckpoints(dataset: DatasetRef, shardNum: Int): Future[Map[Int,Long]] = {
+  def readCheckpoints(dataset: DatasetRef, shardNum: Int): Future[Map[Int, Long]] = {
     checkpointTable.readCheckpoints(dataset, shardNum)
   }
 
   def readEarliestCheckpoint(dataset: DatasetRef, shardNum: Int): Future[Long] = {
-    readCheckpoints(dataset,shardNum) map { m =>
+    readCheckpoints(dataset, shardNum) map { m =>
       if (m.values.isEmpty) Long.MinValue else m.values.min
     }
   }

cassandra/src/main/scala/filodb.cassandra/metastore/CheckpointTable.scala

@@ -76,7 +76,7 @@ sealed class CheckpointTable(val config: Config,
       dataset.dataset, shardNum: JInt, groupNum: JInt, offset: JLong))
   }
 
-  def readCheckpoints(dataset: DatasetRef, shardNum: Int): Future[Map[Int,Long]] = {
+  def readCheckpoints(dataset: DatasetRef, shardNum: Int): Future[Map[Int, Long]] = {
     session.executeAsync(readCheckpointCql.bind(dataset.database.getOrElse(""),
             dataset.dataset, shardNum: JInt))
       .toIterator // future of Iterator

cli/src/main/scala/filodb.cli/CliMain.scala

@@ -13,6 +13,7 @@ import monix.reactive.Observable
 
 import filodb.coordinator._
 import filodb.coordinator.client._
+import filodb.coordinator.client.QueryCommands.{SpreadChange, SpreadProvider, StaticSpreadProvider}
 import filodb.core._
 import filodb.core.metadata.{Column, Dataset, DatasetOptions}
 import filodb.core.store._
@@ -60,6 +61,7 @@ class Arguments extends FieldArgs {
   var ignoreTagsOnPartitionKeyHash: Seq[String] = Nil
   var everyNSeconds: Option[String] = None
   var shards: Option[Seq[String]] = None
+  var spread: Option[Integer] = None
 }
 
 object CliMain extends ArgMain[Arguments] with CsvImportExport with FilodbClusterNode {
@@ -116,7 +118,6 @@ object CliMain extends ArgMain[Arguments] with CsvImportExport with FilodbCluste
     }
 
   def main(args: Arguments): Unit = {
-    val spread = config.getInt("default-spread")
     try {
       val timeout = args.timeoutSeconds.seconds
       args.command match {
@@ -198,15 +199,15 @@ object CliMain extends ArgMain[Arguments] with CsvImportExport with FilodbCluste
           require(args.host.nonEmpty && args.dataset.nonEmpty && args.matcher.nonEmpty, "--host, --dataset and --matcher must be defined")
           val remote = Client.standaloneClient(system, args.host.get, args.port)
           val options = QOptions(args.limit, args.sampleLimit, args.everyNSeconds.map(_.toInt),
-            timeout, args.shards.map(_.map(_.toInt)), spread)
+            timeout, args.shards.map(_.map(_.toInt)), args.spread)
           parseTimeSeriesMetadataQuery(remote, args.matcher.get, args.dataset.get,
             getQueryRange(args), options)
 
         case Some("labelValues") =>
           require(args.host.nonEmpty && args.dataset.nonEmpty && args.labelNames.nonEmpty, "--host, --dataset and --labelName must be defined")
           val remote = Client.standaloneClient(system, args.host.get, args.port)
           val options = QOptions(args.limit, args.sampleLimit, args.everyNSeconds.map(_.toInt),
-            timeout, args.shards.map(_.map(_.toInt)), spread)
+            timeout, args.shards.map(_.map(_.toInt)), args.spread)
           parseLabelValuesQuery(remote, args.labelNames, args.labelFilter, args.dataset.get,
             getQueryRange(args), options)
 
@@ -216,7 +217,7 @@ object CliMain extends ArgMain[Arguments] with CsvImportExport with FilodbCluste
             require(args.host.nonEmpty && args.dataset.nonEmpty, "--host and --dataset must be defined")
             val remote = Client.standaloneClient(system, args.host.get, args.port)
             val options = QOptions(args.limit, args.sampleLimit, args.everyNSeconds.map(_.toInt),
-              timeout, args.shards.map(_.map(_.toInt)), spread)
+              timeout, args.shards.map(_.map(_.toInt)), args.spread)
             parsePromQuery2(remote, query, args.dataset.get, getQueryRange(args), options)
           }.orElse {
             args.select.map { selectCols =>
@@ -267,13 +268,13 @@ object CliMain extends ArgMain[Arguments] with CsvImportExport with FilodbCluste
                     ignoreTagsOnPartitionKeyHash: Seq[String],
                     timeout: FiniteDuration): Unit = {
     try {
-      val datasetObj = Dataset(dataset.dataset, partitionColumns, dataColumns, rowKeys, downsamplers)
       val options = DatasetOptions.DefaultOptions.copy(metricColumn = metricColumn,
                                                        shardKeyColumns = shardKeyColumns,
                                                        ignoreShardKeyColumnSuffixes = ignoreShardKeyColumnSuffixes,
                                                        ignoreTagsOnPartitionKeyHash = ignoreTagsOnPartitionKeyHash)
+      val datasetObj = Dataset(dataset.dataset, partitionColumns, dataColumns, rowKeys, downsamplers, options)
       println(s"Creating dataset $dataset with options $options...")
-      client.createNewDataset(datasetObj.copy(options = options), dataset.database)
+      client.createNewDataset(datasetObj, dataset.database)
       exitCode = 0
     } catch {
       case b: Dataset.BadSchemaError =>
@@ -339,7 +340,7 @@ object CliMain extends ArgMain[Arguments] with CsvImportExport with FilodbCluste
   final case class QOptions(limit: Int, sampleLimit: Int,
                             everyN: Option[Int], timeout: FiniteDuration,
                             shardOverrides: Option[Seq[Int]],
-                            spread: Int)
+                            spread: Option[Integer])
 
   def parseTimeSeriesMetadataQuery(client: LocalClient, query: String, dataset: String,
                                    timeParams: TimeRangeParams,
@@ -364,7 +365,8 @@ object CliMain extends ArgMain[Arguments] with CsvImportExport with FilodbCluste
 
   def executeQuery2(client: LocalClient, dataset: String, plan: LogicalPlan, options: QOptions): Unit = {
     val ref = DatasetRef(dataset)
-    val qOpts = QueryCommands.QueryOptions(options.spread, options.sampleLimit)
+    val spreadProvider: Option[SpreadProvider] = options.spread.map(s => StaticSpreadProvider(SpreadChange(0, s)))
+    val qOpts = QueryCommands.QueryOptions(spreadProvider, options.sampleLimit)
                              .copy(queryTimeoutSecs = options.timeout.toSeconds.toInt,
                                    shardOverrides = options.shardOverrides)
     println(s"Sending query command to server for $ref with options $qOpts...")

conf/histogram-dev-source.conf

@@ -36,9 +36,8 @@
         # Assume 5 bytes per sample, should be roughly equal to (# samples per time series) * (# time series)
         shard-mem-size = 512MB
 
-        # Number of bytes of offheap mem to allocate to write buffers in each shard.  Ex. 1000MB, 1G, 2GB
-        # Scales with the number of time series a shard should hold
-        ingestion-buffer-mem-size = 50MB
+        # Number of bytes of offheap mem to allocate to write buffers for all shards.  Ex. 1000MB, 1G, 2GB
+        ingestion-buffer-mem-size = 200MB
 
         # Number of time series to evict at a time.
         # num-partitions-to-evict = 1000

conf/logback-dev.xml

@@ -29,6 +29,5 @@
 
     <root level="INFO">
         <appender-ref ref="STDOUT"/>
-        <!-- Direct logs to Console in PIE. They get moved to Splunk -->
     </root>
-</configuration>
+</configuration>

conf/timeseries-dev-source.conf

@@ -37,9 +37,12 @@
         # Assume 5 bytes per sample, should be roughly equal to (# samples per time series) * (# time series)
         shard-mem-size = 512MB
 
-        # Number of bytes of offheap mem to allocate to write buffers in each shard.  Ex. 1000MB, 1G, 2GB
-        # Scales with the number of time series a shard should hold
-        ingestion-buffer-mem-size = 50MB
+        # Number of bytes of offheap mem to allocate to write buffers for all shards.  Ex. 1000MB, 1G, 2GB
+        ingestion-buffer-mem-size = 200MB
+
+        # Maximum numer of write buffers to retain in each shard's WriteBufferPool.  Any extra buffers are released
+        # back to native memory, which helps memory reuse.
+        # max-buffer-pool-size = 10000
 
         # Number of time series to evict at a time.
         # num-partitions-to-evict = 1000
@@ -72,6 +75,11 @@
         # Thats about 6MB
         evicted-pk-bloom-filter-capacity = 50000
 
+        # Uncomment to log at DEBUG ingested samples matching these filters on Partition Key columns
+        # Only works for StringColumn fields in the partition key. Scope may be expanded later.
+        # trace-filters = {
+        #   metric = "bad-metric-to-log"
+        # }
       }
       downsample {
         # can be disabled by setting this flag to false

conf/timeseries-ds-1m-dev-source.conf

@@ -33,9 +33,8 @@
         # Assume 5 bytes per sample, should be roughly equal to (# samples per time series) * (# time series)
         shard-mem-size = 512MB
 
-        # Number of bytes of offheap mem to allocate to write buffers in each shard.  Ex. 1000MB, 1G, 2GB
-        # Scales with the number of time series a shard should hold
-        ingestion-buffer-mem-size = 50MB
+        # Number of bytes of offheap mem to allocate to write buffers for all shards.  Ex. 1000MB, 1G, 2GB
+        ingestion-buffer-mem-size = 200MB
 
         # Number of time series to evict at a time.
         # num-partitions-to-evict = 1000

conf/timeseries-filodb-server.conf

@@ -5,6 +5,19 @@ filodb {
     port = 9042
     partition-list-num-groups = 1
   }
+  spread-default = 1
+
+  # Override default spread for application using override block which will have non metric shard keys and spread.
+  spread-assignment = [
+    {
+      _ns = App-0,
+      _spread_ = 2
+    },
+    {
+      _ns = App-5,
+      _spread_ = 0
+    }
+  ]
 }
 
 kamon {

conf/timeseries-standalonetest-source.conf

@@ -18,7 +18,7 @@
         max-chunks-size = 400
 
         shard-mem-size = 512MB
-        ingestion-buffer-mem-size = 50MB
+        ingestion-buffer-mem-size = 200MB
         groups-per-shard = 20
         multi-partition-odp = false
       }