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  "removedHistoricalFiles": [
    "part-00000-62341c08-96d8-43a9-bcf1-5f1f6bd91945-c000.snappy.parquet"
  ],
  "historicalError": "org.apache.spark.SparkException: Job aborted due to stage failure: Task 1 in stage 168.0 failed 1 times, most recent failure: Lost task 1.0 in stage 168.0 (TID 127) (ayo-mbp.tailb899c1.ts.net executor driver): org.apache.spark.SparkFileNotFoundException: File file:<temporary>/table/part-00000-62341c08-96d8-43a9-bcf1-5f1f6bd91945-c000.snappy.parquet does not exist\nIt is possible the underlying files have been updated. You can explicitly invalidate the cache in Spark by running 'REFRESH TABLE tableName' command in SQL or by recreating the Dataset/DataFrame involved.\n\tat org.apache.spark.sql.errors.QueryExecutionErrors$.readCurrentFileNotFoundError(QueryExecutionErrors.scala:781)\n\tat org.apache.spark.sql.execution.datasources.FileScanRDD$$anon$1.org$apache$spark$sql$execution$datasources$FileScanRDD$$anon$$readCurrentFile(FileScanRDD.scala:222)\n\tat org.apache.spark.sql.execution.datasources.FileScanRDD$$anon$1.nextIterator(FileScanRDD.scala:282)\n\tat org.apache.spark.sql.execution.datasources.FileScanRDD$$anon$1.hasNext(FileScanRDD.scala:131)\n\tat org.apache.spark.sql.execution.FileSourceScanExec$$anon$1.hasNext(DataSourceScanExec.scala:593)\n\tat org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIteratorForCodegenStage1.columnartorow_nextBatch_0$(Unknown Source)\n\tat org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIteratorForCodegenStage1.processNext(Unknown Source)\n\tat org.apache.spark.sql.execution.BufferedRowIterator.hasNext(BufferedRowIterator.java:43)\n\tat org.apache.spark.sql.execution.WholeStageCodegenEvaluatorFactory$WholeStageCodegenPartitionEvaluator$$anon$1.hasNext(WholeStageCodegenEvaluatorFactory.scala:43)\n\tat scala.collection.Iterator$$anon$10.hasNext(Iterator.scala:460)\n\tat scala.collection.Iterator$$anon$10.hasNext(Iterator.scala:460)\n\tat org.apache.spark.util.random.SamplingUtils$.reservoirSampleAndCount(SamplingUtils.scala:41)\n\tat org.apache.spark.RangePartitioner$.$anonfun$sketch$1(Partitioner.scala:322)\n\tat org.apache.spark.RangePartitioner$.$anonfun$sketch$1$adapted(Partitioner.scala:320)\n\tat org.apache.spark.rdd.RDD.$anonfun$mapPartitionsWithIndex$2(RDD.scala:910)\n\tat org.apache.spark.rdd.RDD.$anonfun$mapPartitionsWithIndex$2$adapted(RDD.scala:910)\n\tat org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:52)\n\tat org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:367)\n\tat org.apache.spark.rdd.RDD.iterator(RDD.scala:331)\n\tat org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:93)\n\tat org.apache.spark.TaskContext.runTaskWithListeners(TaskContext.scala:166)\n\tat org.apache.spark.scheduler.Task.run(Task.scala:141)\n\tat org.apache.spark.executor.Executor$TaskRunner.$anonfun$run$4(Executor.scala:621)\n\tat org.apache.spark.util.SparkErrorUtils.tryWithSafeFinally(SparkErrorUtils.scala:64)\n\tat org.apache.spark.util.SparkErrorUtils.tryWithSafeFinally$(SparkErrorUtils.scala:61)\n\tat org.apache.spark.util.Utils$.tryWithSafeFinally(Utils.scala:94)\n\tat org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:624)\n\tat java.base/java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1136)\n\tat java.base/java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:635)\n\tat java.base/java.lang.Thread.run(Thread.java:840)\n\nDriver stacktrace:",
  "semantic": {
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    "activeVectorCounts": [
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    "currentRowsUnchanged": true,
    "cleanupOperations": [
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      "VACUUM END"
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    "reorgIdempotent": true,
    "oldMembershipReconstructible": true,
    "historicalReadFails": true
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