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Prototype of HdfsJsonScanner implemented based on rapidjson, which supports scanning data from splitting json files. The scanning of JSON data is mainly completed by two parts working together. The first part is the JsonParser responsible for parsing the JSON object, which is implemented based on the SAX-style API of rapidjson. It reads data from the char stream, parses it, and calls the corresponding callback function when encountering the corresponding JSON element. See the comments of the JsonParser class for more details. The other part is the HdfsJsonScanner, which inherits from HdfsScanner and provides callback functions for the JsonParser. The callback functions are responsible for providing data buffers to the Parser and converting and materializing the Parser's parsing results into RowBatch. It should be noted that the parser returns numeric values as strings to the scanner. The scanner uses the TextConverter class to convert the strings to the desired types, similar to how the HdfsTextScanner works. This is an advantage compared to using number value provided by rapidjson directly, as it eliminates concerns about inconsistencies in converting decimals (e.g. losing precision). Added a startup flag, enable_json_scanner, to be able to disable this feature if we hit critical bugs in production. Limitations - Multiline json objects are not fully supported yet. It is ok when each file has only one scan range. However, when a file has multiple scan ranges, there is a small probability of incomplete scanning of multiline JSON objects that span ScanRange boundaries (in such cases, parsing errors may be reported). For more details, please refer to the comments in the 'multiline_json.test'. - Compressed JSON files are not supported yet. - Complex types are not supported yet. Tests - Most of the existing end-to-end tests can run on JSON format. - Add TestQueriesJsonTables in test_queries.py for testing multiline, malformed, and overflow in JSON. Change-Id: I31309cb8f2d04722a0508b3f9b8f1532ad49a569 Reviewed-on: http://gerrit.cloudera.org:8080/19699 Reviewed-by: Quanlong Huang <huangquanlong@gmail.com> Tested-by: Impala Public Jenkins <impala-public-jenkins@cloudera.com>
654 lines
27 KiB
Bash
Executable File
654 lines
27 KiB
Bash
Executable File
#!/bin/bash
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#
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# Licensed to the Apache Software Foundation (ASF) under one
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# or more contributor license agreements. See the NOTICE file
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# distributed with this work for additional information
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# regarding copyright ownership. The ASF licenses this file
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# to you under the Apache License, Version 2.0 (the
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# "License"); you may not use this file except in compliance
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# with the License. You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing,
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# software distributed under the License is distributed on an
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# "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
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# KIND, either express or implied. See the License for the
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# specific language governing permissions and limitations
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# under the License.
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#
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# This script can be executed in two ways:
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# 1) Without any command line parameters - A normal data load will happen where data is
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# generated as needed, generally by issuing 'INSERT INTO <table> SELECT *' commands.
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# 2) With a command line parameter pointing to a test-warehouse snapshot file - In this
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# case the snapshot file contents will be copied into HDFS prior to calling the data load
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# scripts. This speeds up overall data loading time because it usually means only the
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# table metadata needs to be created.
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#
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# For more information look at testdata/bin/load-test-warehouse-snapshot.sh and
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# bin/load-data.py
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set -euo pipefail
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. $IMPALA_HOME/bin/report_build_error.sh
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setup_report_build_error
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. ${IMPALA_HOME}/bin/impala-config.sh > /dev/null 2>&1
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. ${IMPALA_HOME}/testdata/bin/run-step.sh
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# Environment variables used to direct the data loading process to an external cluster.
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# TODO: We need a better way of managing how these get set. See IMPALA-4346
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: ${HS2_HOST_PORT=localhost:11050}
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: ${HDFS_NN=${INTERNAL_LISTEN_HOST}:20500}
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: ${IMPALAD=localhost}
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: ${REMOTE_LOAD=}
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: ${CM_HOST=}
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: ${IMPALA_SERIAL_DATALOAD=}
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# We don't expect dataload to take more than 2.5 hours.
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: ${TIMEOUT_FOR_CREATE_LOAD_DATA_MINS:= 150}
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SKIP_METADATA_LOAD=0
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SKIP_SNAPSHOT_LOAD=0
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SKIP_RANGER=0
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SNAPSHOT_FILE=""
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LOAD_DATA_ARGS=""
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EXPLORATION_STRATEGY="exhaustive"
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export JDBC_URL="jdbc:hive2://${HS2_HOST_PORT}/default;"
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HIVE_CMD="beeline -n $USER -u $JDBC_URL"
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# For logging when using run-step.
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LOG_DIR=${IMPALA_DATA_LOADING_LOGS_DIR}
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echo "Executing: create-load-data.sh $@"
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while [ -n "$*" ]
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do
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case $1 in
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-exploration_strategy)
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EXPLORATION_STRATEGY=${2-}
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if [[ -z "$EXPLORATION_STRATEGY" ]]; then
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echo "Must provide an exploration strategy from e.g. core, exhaustive"
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exit 1;
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fi
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shift;
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;;
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-skip_metadata_load)
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SKIP_METADATA_LOAD=1
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;;
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-skip_snapshot_load)
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SKIP_SNAPSHOT_LOAD=1
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;;
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-snapshot_file)
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SNAPSHOT_FILE=${2-}
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if [ ! -f $SNAPSHOT_FILE ]; then
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echo "-snapshot_file does not exist: $SNAPSHOT_FILE"
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exit 1;
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fi
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shift;
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;;
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-cm_host)
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CM_HOST=${2-}
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shift;
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;;
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-skip_ranger)
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SKIP_RANGER=1
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;;
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-timeout)
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TIMEOUT_FOR_CREATE_LOAD_DATA_MINS=${2-}
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shift;
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;;
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-help|-h|*)
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echo "create-load-data.sh : Creates data and loads from scratch"
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echo "[-skip_metadata_load] : Skips loading of metadata"
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echo "[-skip_snapshot_load] : Assumes that the snapshot is already loaded"
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echo "[-snapshot_file] : Loads the test warehouse snapshot into hdfs"
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echo "[-cm_host] : Address of the Cloudera Manager host if loading to a remote cluster"
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echo "[-skip_ranger] : Skip the set-up for Ranger."
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echo "[-timeout] : The timeout in minutes for loading data."
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exit 1;
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;;
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esac
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shift;
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done
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if [[ -n $REMOTE_LOAD ]]; then
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SKIP_RANGER=1
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fi
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"${IMPALA_HOME}/bin/script-timeout-check.sh" -timeout $TIMEOUT_FOR_CREATE_LOAD_DATA_MINS \
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-script_name "$(basename $0)" &
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TIMEOUT_PID=$!
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SCHEMA_MISMATCH_ERROR="A schema change has been detected in the metadata, "
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SCHEMA_MISMATCH_ERROR+="but it cannot be loaded on Isilon, s3, gcs, cos, oss, obs or "
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SCHEMA_MISMATCH_ERROR+="local filesystem, and the filesystem is ${TARGET_FILESYSTEM}".
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if [[ $SKIP_METADATA_LOAD -eq 0 && "$SNAPSHOT_FILE" = "" ]]; then
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run-step "Generating HBase data" create-hbase.log \
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${IMPALA_HOME}/testdata/bin/create-hbase.sh
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run-step "Creating /test-warehouse HDFS directory" create-test-warehouse-dir.log \
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hadoop fs -mkdir -p /test-warehouse
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elif [ $SKIP_SNAPSHOT_LOAD -eq 0 ]; then
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run-step "Loading HDFS data from snapshot: $SNAPSHOT_FILE" \
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load-test-warehouse-snapshot.log \
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${IMPALA_HOME}/testdata/bin/load-test-warehouse-snapshot.sh "$SNAPSHOT_FILE"
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# Don't skip the metadata load if a schema change is detected.
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if ! ${IMPALA_HOME}/testdata/bin/check-schema-diff.sh; then
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if [[ "${TARGET_FILESYSTEM}" == "isilon" || "${TARGET_FILESYSTEM}" == "s3" || \
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"${TARGET_FILESYSTEM}" == "local" || "${TARGET_FILESYSTEM}" == "gs" || \
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"${TARGET_FILESYSTEM}" == "cosn" || "${TARGET_FILESYSTEM}" == "oss" || \
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"${TARGET_FILESYSTEM}" == "obs" || "${TARGET_FILESYSTEM}" == "ozone" ]] ; then
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echo "ERROR in $0 at line $LINENO: A schema change has been detected in the"
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echo "metadata, but it cannot be loaded on isilon, s3, gcs, cos, oss, obs, ozone,"
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echo "or local and the target file system is ${TARGET_FILESYSTEM}. Exiting."
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# Generate an explicit JUnitXML symptom report here for easier triaging
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${IMPALA_HOME}/bin/generate_junitxml.py --phase=dataload \
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--step=check-schema-diff.sh --error "${SCHEMA_MISMATCH_ERROR}"
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exit 1
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fi
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echo "Schema change detected, metadata will be loaded."
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SKIP_METADATA_LOAD=0
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fi
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else
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# hdfs data already exists, don't load it.
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echo Skipping loading data to hdfs.
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fi
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echo "Derived params for create-load-data.sh:"
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echo "EXPLORATION_STRATEGY=${EXPLORATION_STRATEGY:-}"
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echo "SKIP_METADATA_LOAD=${SKIP_METADATA_LOAD:-}"
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echo "SKIP_SNAPSHOT_LOAD=${SKIP_SNAPSHOT_LOAD:-}"
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echo "SNAPSHOT_FILE=${SNAPSHOT_FILE:-}"
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echo "CM_HOST=${CM_HOST:-}"
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echo "REMOTE_LOAD=${REMOTE_LOAD:-}"
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function start-impala {
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: ${START_CLUSTER_ARGS=""}
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# Use a fast statestore update so that DDL operations run faster.
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START_CLUSTER_ARGS_INT="--state_store_args=--statestore_update_frequency_ms=50"
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if [[ "${TARGET_FILESYSTEM}" == "local" ]]; then
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START_CLUSTER_ARGS_INT+=("--impalad_args=--abort_on_config_error=false -s 1")
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else
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START_CLUSTER_ARGS_INT+=("-s 3")
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fi
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START_CLUSTER_ARGS_INT+=("${START_CLUSTER_ARGS}")
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${IMPALA_HOME}/bin/start-impala-cluster.py --log_dir=${IMPALA_DATA_LOADING_LOGS_DIR} \
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${START_CLUSTER_ARGS_INT[@]}
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}
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function restart-cluster {
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# Break out each individual step for clarity
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echo "Shutting down Impala"
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${IMPALA_HOME}/bin/start-impala-cluster.py --kill
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echo "Shutting down the minicluster"
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${IMPALA_HOME}/testdata/bin/kill-all.sh
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echo "Starting the minicluster"
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${IMPALA_HOME}/testdata/bin/run-all.sh
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echo "Starting Impala"
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start-impala
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}
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function load-custom-schemas {
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# HDFS commandline calls are slow, so consolidate the manipulation into
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# as few calls as possible by populating a temporary directory with the
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# appropriate structure and copying it in a single call.
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TMP_DIR=$(mktemp -d)
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# Cleanup old schemas dir
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hadoop fs -rm -r -f /test-warehouse/schemas
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SCHEMA_SRC_DIR=${IMPALA_HOME}/testdata/data/schemas
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SCHEMA_TMP_DIR="${TMP_DIR}/schemas"
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mkdir ${SCHEMA_TMP_DIR}
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mkdir ${SCHEMA_TMP_DIR}/enum
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ln -s ${SCHEMA_SRC_DIR}/zipcode_incomes.parquet ${SCHEMA_TMP_DIR}
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ln -s ${SCHEMA_SRC_DIR}/alltypestiny.parquet ${SCHEMA_TMP_DIR}
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ln -s ${SCHEMA_SRC_DIR}/enum/* ${SCHEMA_TMP_DIR}/enum
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ln -s ${SCHEMA_SRC_DIR}/malformed_decimal_tiny.parquet ${SCHEMA_TMP_DIR}
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ln -s ${SCHEMA_SRC_DIR}/decimal.parquet ${SCHEMA_TMP_DIR}
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ln -s ${SCHEMA_SRC_DIR}/nested/modern_nested.parquet ${SCHEMA_TMP_DIR}
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ln -s ${SCHEMA_SRC_DIR}/nested/legacy_nested.parquet ${SCHEMA_TMP_DIR}
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# CHAR and VARCHAR tables written by Hive
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mkdir -p ${TMP_DIR}/chars_formats_avro_snap \
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${TMP_DIR}/chars_formats_parquet \
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${TMP_DIR}/chars_formats_text \
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${TMP_DIR}/chars_formats_orc_def \
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${TMP_DIR}/chars_formats_json
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ln -s ${IMPALA_HOME}/testdata/data/chars-formats.avro ${TMP_DIR}/chars_formats_avro_snap
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ln -s ${IMPALA_HOME}/testdata/data/chars-formats.parquet ${TMP_DIR}/chars_formats_parquet
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ln -s ${IMPALA_HOME}/testdata/data/chars-formats.orc ${TMP_DIR}/chars_formats_orc_def
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ln -s ${IMPALA_HOME}/testdata/data/chars-formats.txt ${TMP_DIR}/chars_formats_text
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ln -s ${IMPALA_HOME}/testdata/data/chars-formats.json ${TMP_DIR}/chars_formats_json
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# File used by CreateTableLikeOrc tests
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ln -s ${IMPALA_HOME}/testdata/data/alltypes_non_acid.orc ${SCHEMA_TMP_DIR}
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hadoop fs -put -f ${TMP_DIR}/* /test-warehouse
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rm -r ${TMP_DIR}
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}
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function load-data {
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WORKLOAD=${1}
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EXPLORATION_STRATEGY=${2:-"core"}
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TABLE_FORMATS=${3:-}
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FORCE_LOAD=${4:-}
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MSG="Loading workload '$WORKLOAD'"
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ARGS=("--workloads $WORKLOAD")
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MSG+=" using exploration strategy '$EXPLORATION_STRATEGY'"
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ARGS+=("-e $EXPLORATION_STRATEGY")
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if [ $TABLE_FORMATS ]; then
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MSG+=" in table formats '$TABLE_FORMATS'"
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ARGS+=("--table_formats $TABLE_FORMATS")
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fi
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if [ $LOAD_DATA_ARGS ]; then
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ARGS+=("$LOAD_DATA_ARGS")
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fi
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# functional-query is unique. The dataset name is not the same as the workload name.
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if [ "${WORKLOAD}" = "functional-query" ]; then
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WORKLOAD="functional"
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fi
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# TODO: Why is there a REMOTE_LOAD condition? See IMPALA-4347
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#
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# Force load the dataset if we detect a schema change.
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if [[ -z "$REMOTE_LOAD" ]]; then
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if ! ${IMPALA_HOME}/testdata/bin/check-schema-diff.sh $WORKLOAD; then
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ARGS+=("--force")
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echo "Force loading $WORKLOAD because a schema change was detected"
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elif [ "${FORCE_LOAD}" = "force" ]; then
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ARGS+=("--force")
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echo "Force loading."
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fi
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fi
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ARGS+=("--impalad ${IMPALAD}")
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ARGS+=("--hive_hs2_hostport ${HS2_HOST_PORT}")
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ARGS+=("--hdfs_namenode ${HDFS_NN}")
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# Disable parallelism for dataload if IMPALA_SERIAL_DATALOAD is set
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if [[ "${IMPALA_SERIAL_DATALOAD}" -eq 1 ]]; then
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ARGS+=("--num_processes 1")
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fi
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if [[ -n ${TABLE_FORMATS} ]]; then
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# TBL_FMT_STR replaces slashes with underscores,
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# e.g., kudu/none/none -> kudu_none_none
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TBL_FMT_STR=${TABLE_FORMATS//[\/]/_}
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LOG_BASENAME=data-load-${WORKLOAD}-${EXPLORATION_STRATEGY}-${TBL_FMT_STR}.log
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else
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LOG_BASENAME=data-load-${WORKLOAD}-${EXPLORATION_STRATEGY}.log
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fi
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LOG_FILE=${IMPALA_DATA_LOADING_LOGS_DIR}/${LOG_BASENAME}
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echo "$MSG. Logging to ${LOG_FILE}"
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# Use unbuffered logging by executing with -u
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if ! impala-python -u ${IMPALA_HOME}/bin/load-data.py ${ARGS[@]} &> ${LOG_FILE}; then
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echo Error loading data. The end of the log file is:
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tail -n 50 $LOG_FILE
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return 1
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fi
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}
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function cache-test-tables {
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echo CACHING tpch.nation AND functional.alltypestiny
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# uncaching the tables first makes this operation idempotent.
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${IMPALA_HOME}/bin/impala-shell.sh -i ${IMPALAD}\
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-q "alter table functional.alltypestiny set uncached"
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${IMPALA_HOME}/bin/impala-shell.sh -i ${IMPALAD}\
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-q "alter table tpch.nation set uncached"
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${IMPALA_HOME}/bin/impala-shell.sh -i ${IMPALAD}\
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-q "alter table tpch.nation set cached in 'testPool'"
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${IMPALA_HOME}/bin/impala-shell.sh -i ${IMPALAD} -q\
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"alter table functional.alltypestiny set cached in 'testPool'"
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}
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function load-aux-workloads {
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LOG_FILE=${IMPALA_DATA_LOADING_LOGS_DIR}/data-load-auxiliary-workloads-core.log
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rm -f $LOG_FILE
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# Load all the auxiliary workloads (if any exist)
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if [ -d ${IMPALA_AUX_WORKLOAD_DIR} ] && [ -d ${IMPALA_AUX_DATASET_DIR} ]; then
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echo Loading auxiliary workloads. Logging to $LOG_FILE.
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if ! impala-python -u ${IMPALA_HOME}/bin/load-data.py --workloads all\
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--impalad=${IMPALAD}\
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--hive_hs2_hostport=${HS2_HOST_PORT}\
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--hdfs_namenode=${HDFS_NN}\
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--workload_dir=${IMPALA_AUX_WORKLOAD_DIR}\
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--dataset_dir=${IMPALA_AUX_DATASET_DIR}\
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--exploration_strategy=core ${LOAD_DATA_ARGS} >> $LOG_FILE 2>&1; then
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echo Error loading aux workloads. The end of the log file is:
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tail -n 20 $LOG_FILE
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return 1
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fi
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else
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echo "Skipping load of auxilary workloads because directories do not exist"
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fi
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}
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function copy-and-load-dependent-tables {
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# COPY
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# TODO: The multi-format table will move these files. So we need to copy them to a
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# temporary location for that table to use. Should find a better way to handle this.
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echo COPYING AND LOADING DATA FOR DEPENDENT TABLES
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hadoop fs -rm -r -f /test-warehouse/alltypesmixedformat \
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/tmp/alltypes_rc /tmp/alltypes_seq /tmp/alltypes_parquet
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hadoop fs -mkdir -p /tmp/alltypes_seq/year=2009 \
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/tmp/alltypes_rc/year=2009 /tmp/alltypes_parquet/year=2009
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# The file written by hive to /test-warehouse will be strangely replicated rather than
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# erasure coded if EC is not set in /tmp
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if [[ -n "${HDFS_ERASURECODE_POLICY:-}" ]]; then
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hdfs ec -setPolicy -policy "${HDFS_ERASURECODE_POLICY}" -path "/tmp/alltypes_rc"
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hdfs ec -setPolicy -policy "${HDFS_ERASURECODE_POLICY}" -path "/tmp/alltypes_seq"
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hdfs ec -setPolicy -policy "${HDFS_ERASURECODE_POLICY}" -path "/tmp/alltypes_parquet"
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fi
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hadoop fs -cp /test-warehouse/alltypes_seq/year=2009/month=2/ /tmp/alltypes_seq/year=2009
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hadoop fs -cp /test-warehouse/alltypes_rc/year=2009/month=3/ /tmp/alltypes_rc/year=2009
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hadoop fs -cp /test-warehouse/alltypes_parquet/year=2009/month=4/ /tmp/alltypes_parquet/year=2009
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# Create a hidden file in AllTypesSmall
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hadoop fs -cp -f /test-warehouse/zipcode_incomes/DEC_00_SF3_P077_with_ann_noheader.csv \
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/test-warehouse/alltypessmall/year=2009/month=1/_hidden
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hadoop fs -cp -f /test-warehouse/zipcode_incomes/DEC_00_SF3_P077_with_ann_noheader.csv \
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/test-warehouse/alltypessmall/year=2009/month=1/.hidden
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# In case the data is updated by a non-super user, make sure the user can write
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# by chmoding 777 /tmp/alltypes_rc and /tmp/alltypes_seq. This is needed in order
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# to prevent this error during data load to a remote cluster:
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#
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# ERROR : Failed with exception Unable to move source hdfs://cluster-1.foo.cloudera.com:
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# 8020/tmp/alltypes_seq/year=2009/month=2/000023_0 to destination hdfs://cluster-1.foo.
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# cloudera.com:8020/test-warehouse/alltypesmixedformat/year=2009/month=2/000023_0
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# [...]
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# Caused by: org.apache.hadoop.security.AccessControlException:
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# Permission denied: user=impala, access=WRITE
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# inode="/tmp/alltypes_seq/year=2009/month=2":hdfs:supergroup:drwxr-xr-x
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#
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# The error occurs while loading dependent tables.
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#
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# See: logs/data_loading/copy-and-load-dependent-tables.log)
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# See also: IMPALA-4345
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hadoop fs -chmod -R 777 /tmp/alltypes_rc /tmp/alltypes_seq /tmp/alltypes_parquet
|
|
|
|
# For tables that rely on loading data from local fs test-wareload-house
|
|
# TODO: Find a good way to integrate this with the normal data loading scripts
|
|
beeline -n $USER -u "${JDBC_URL}" -f\
|
|
${IMPALA_HOME}/testdata/bin/load-dependent-tables.sql
|
|
}
|
|
|
|
function create-internal-hbase-table {
|
|
# TODO: For some reason DROP TABLE IF EXISTS sometimes fails on HBase if the table does
|
|
# not exist. To work around this, disable exit on error before executing this command.
|
|
# Need to investigate this more, but this works around the problem to unblock automation.
|
|
set +o errexit
|
|
beeline -n $USER -u "${JDBC_URL}" -e\
|
|
"DROP TABLE IF EXISTS functional_hbase.internal_hbase_table;"
|
|
echo "disable 'functional_hbase.internal_hbase_table'" | hbase shell
|
|
echo "drop 'functional_hbase.internal_hbase_table'" | hbase shell
|
|
set -e
|
|
# Used by CatalogTest to confirm that non-external HBase tables are identified
|
|
# correctly (IMP-581)
|
|
# Note that the usual 'hbase.table.name' property is not specified to avoid
|
|
# creating tables in HBase as a side-effect.
|
|
cat > /tmp/create-hbase-internal.sql << EOF
|
|
CREATE TABLE functional_hbase.internal_hbase_table(key int, value string)
|
|
STORED BY 'org.apache.hadoop.hive.hbase.HBaseStorageHandler'
|
|
WITH SERDEPROPERTIES ("hbase.columns.mapping" = ":key,cf1:val");
|
|
EOF
|
|
beeline -n $USER -u "${JDBC_URL}" -f /tmp/create-hbase-internal.sql
|
|
rm -f /tmp/create-hbase-internal.sql
|
|
}
|
|
|
|
function load-custom-data {
|
|
# Add a sequence file that only contains a header (see IMPALA-362)
|
|
hadoop fs -put -f ${IMPALA_HOME}/testdata/tinytable_seq_snap/tinytable_seq_snap_header_only \
|
|
/test-warehouse/tinytable_seq_snap
|
|
|
|
# IMPALA-1619: payload compressed with snappy used for constructing large snappy block
|
|
# compressed file
|
|
hadoop fs -put -f ${IMPALA_HOME}/testdata/compressed_formats/compressed_payload.snap \
|
|
/test-warehouse/compressed_payload.snap
|
|
|
|
# Create Avro tables
|
|
beeline -n $USER -u "${JDBC_URL}" -f\
|
|
${IMPALA_HOME}/testdata/avro_schema_resolution/create_table.sql
|
|
|
|
# Delete potentially existing avro data
|
|
hadoop fs -rm -f /test-warehouse/avro_schema_resolution_test/*.avro
|
|
|
|
# Upload Avro data to the 'schema_resolution_test' table
|
|
hadoop fs -put ${IMPALA_HOME}/testdata/avro_schema_resolution/records*.avro \
|
|
/test-warehouse/avro_schema_resolution_test
|
|
}
|
|
|
|
function build-and-copy-hive-udfs {
|
|
# Build the test Hive UDFs
|
|
pushd ${IMPALA_HOME}/java/test-hive-udfs
|
|
${IMPALA_HOME}/bin/mvn-quiet.sh clean
|
|
${IMPALA_HOME}/bin/mvn-quiet.sh package
|
|
popd
|
|
# Copy the test UDF/UDA libraries into HDFS
|
|
${IMPALA_HOME}/testdata/bin/copy-udfs-udas.sh -build
|
|
}
|
|
|
|
# Additional data loading actions that must be executed after the main data is loaded.
|
|
function custom-post-load-steps {
|
|
# TODO: Why is there a REMOTE_LOAD condition? See IMPALA-4347
|
|
if [[ -z "$REMOTE_LOAD" ]]; then
|
|
# Configure alltypes_seq as a read-only table. This is required for fe tests.
|
|
# Set both read and execute permissions because accessing the contents of a directory on
|
|
# the local filesystem requires the x permission (while on HDFS it requires the r
|
|
# permission).
|
|
hadoop fs -chmod -R 555 \
|
|
${FILESYSTEM_PREFIX}/test-warehouse/alltypes_seq/year=2009/month=1 \
|
|
${FILESYSTEM_PREFIX}/test-warehouse/alltypes_seq/year=2009/month=3
|
|
fi
|
|
|
|
hadoop fs -mkdir -p ${FILESYSTEM_PREFIX}/test-warehouse/lineitem_multiblock_parquet \
|
|
${FILESYSTEM_PREFIX}/test-warehouse/lineitem_sixblocks_parquet \
|
|
${FILESYSTEM_PREFIX}/test-warehouse/lineitem_multiblock_one_row_group_parquet \
|
|
${FILESYSTEM_PREFIX}/test-warehouse/lineitem_multiblock_variable_num_rows_parquet
|
|
|
|
#IMPALA-1881: data file produced by hive with multiple blocks.
|
|
hadoop fs -Ddfs.block.size=1048576 -put -f \
|
|
${IMPALA_HOME}/testdata/LineItemMultiBlock/000000_0 \
|
|
${FILESYSTEM_PREFIX}/test-warehouse/lineitem_multiblock_parquet
|
|
|
|
# IMPALA-2466: Add more tests to the HDFS Parquet scanner (Added after IMPALA-1881)
|
|
hadoop fs -Ddfs.block.size=1048576 -put -f \
|
|
${IMPALA_HOME}/testdata/LineItemMultiBlock/lineitem_sixblocks.parquet \
|
|
${FILESYSTEM_PREFIX}/test-warehouse/lineitem_sixblocks_parquet
|
|
|
|
# IMPALA-2466: Add more tests to the HDFS Parquet scanner (this has only one row group)
|
|
hadoop fs -Ddfs.block.size=1048576 -put -f \
|
|
${IMPALA_HOME}/testdata/LineItemMultiBlock/lineitem_one_row_group.parquet \
|
|
${FILESYSTEM_PREFIX}/test-warehouse/lineitem_multiblock_one_row_group_parquet
|
|
|
|
# IMPALA-11350: Add tests for row groups with variable num rows.
|
|
hadoop fs -Ddfs.block.size=1048576 -put -f \
|
|
${IMPALA_HOME}/testdata/LineItemMultiBlock/lineitem_multiblock_variable_num_rows.parquet \
|
|
${FILESYSTEM_PREFIX}/test-warehouse/lineitem_multiblock_variable_num_rows_parquet
|
|
|
|
# IMPALA-3307: Upload test time-zone database
|
|
hadoop fs -Ddfs.block.size=1048576 -put -f ${IMPALA_HOME}/testdata/tzdb \
|
|
${FILESYSTEM_PREFIX}/test-warehouse/
|
|
}
|
|
|
|
function copy-and-load-ext-data-source {
|
|
# Copy the test data source library into HDFS
|
|
${IMPALA_HOME}/testdata/bin/copy-data-sources.sh
|
|
# Create data sources table.
|
|
${IMPALA_HOME}/bin/impala-shell.sh -i ${IMPALAD} -f\
|
|
${IMPALA_HOME}/testdata/bin/create-data-source-table.sql
|
|
}
|
|
|
|
function check-hdfs-health {
|
|
if [[ -n "${HDFS_ERASURECODE_POLICY:-}" ]]; then
|
|
if ! grep "Replicated Blocks:[[:space:]]*#[[:space:]]*Total size:[[:space:]]*0 B"\
|
|
<<< $(hdfs fsck /test-warehouse | tr '\n' '#'); then
|
|
echo "There are some replicated files despite that erasure coding is on"
|
|
echo "Failing the data loading job"
|
|
exit 1
|
|
fi
|
|
return
|
|
fi
|
|
MAX_FSCK=30
|
|
SLEEP_SEC=120
|
|
LAST_NUMBER_UNDER_REPLICATED=-1
|
|
for ((FSCK_COUNT = 0; FSCK_COUNT <= MAX_FSCK; FSCK_COUNT++)); do
|
|
FSCK_OUTPUT="$(hdfs fsck /test-warehouse)"
|
|
echo "$FSCK_OUTPUT"
|
|
NUMBER_UNDER_REPLICATED=$(
|
|
grep -oP "Under-replicated blocks:[[:space:]]*\K[[:digit:]]*" <<< "$FSCK_OUTPUT")
|
|
if [[ "$NUMBER_UNDER_REPLICATED" -eq 0 ]] ; then
|
|
# All the blocks are fully-replicated. The data loading can continue.
|
|
return
|
|
fi
|
|
if [[ $(($FSCK_COUNT + 1)) -eq "$MAX_FSCK" ]] ; then
|
|
echo "Some HDFS blocks are still under-replicated after running HDFS fsck"\
|
|
"$MAX_FSCK times."
|
|
echo "Some tests cannot pass without fully-replicated blocks (IMPALA-3887)."
|
|
echo "Failing the data loading."
|
|
exit 1
|
|
fi
|
|
if [[ "$NUMBER_UNDER_REPLICATED" -eq "$LAST_NUMBER_UNDER_REPLICATED" ]] ; then
|
|
echo "There are under-replicated blocks in HDFS and HDFS is not making progress"\
|
|
"in $SLEEP_SEC seconds. Attempting to restart HDFS to resolve this issue."
|
|
# IMPALA-7119: Other minicluster components (like HBase) can fail if HDFS is
|
|
# restarted by itself, so restart the whole cluster, including Impala.
|
|
restart-cluster
|
|
fi
|
|
LAST_NUMBER_UNDER_REPLICATED="$NUMBER_UNDER_REPLICATED"
|
|
echo "$NUMBER_UNDER_REPLICATED under replicated blocks remaining."
|
|
echo "Sleeping for $SLEEP_SEC seconds before rechecking."
|
|
sleep "$SLEEP_SEC"
|
|
done
|
|
}
|
|
|
|
function warm-up-hive {
|
|
echo "Running warm up Hive statements"
|
|
$HIVE_CMD -e "create database if not exists functional;"
|
|
$HIVE_CMD -e "create table if not exists hive_warm_up_tbl (i int);"
|
|
# The insert below starts a Tez session (if Hive uses Tez) and initializes
|
|
# .hiveJars directory in HDFS, see IMPALA-8841.
|
|
$HIVE_CMD -e "insert overwrite table hive_warm_up_tbl values (1);"
|
|
}
|
|
|
|
# For kerberized clusters, use kerberos
|
|
if ${CLUSTER_DIR}/admin is_kerberized; then
|
|
LOAD_DATA_ARGS="${LOAD_DATA_ARGS} --use_kerberos --principal=${MINIKDC_PRINC_HIVE}"
|
|
fi
|
|
|
|
# Start Impala
|
|
if [[ -z "$REMOTE_LOAD" ]]; then
|
|
run-step "Starting Impala cluster" start-impala-cluster.log start-impala
|
|
fi
|
|
|
|
# The hdfs environment script sets up kms (encryption) and cache pools (hdfs caching).
|
|
# On a non-hdfs filesystem, we don't test encryption or hdfs caching, so this setup is not
|
|
# needed.
|
|
if [[ "${TARGET_FILESYSTEM}" == "hdfs" ]]; then
|
|
run-step "Setting up HDFS environment" setup-hdfs-env.log \
|
|
${IMPALA_HOME}/testdata/bin/setup-hdfs-env.sh
|
|
fi
|
|
|
|
if [ $SKIP_METADATA_LOAD -eq 0 ]; then
|
|
# Using Hive in non-parallel mode before starting parallel execution may help with some
|
|
# flakiness during data load, see IMPALA-8841. The problem only occurs in Hive 3
|
|
# environment, but always doing the warm up shouldn't hurt much and may make it easier
|
|
# to investigate future issues where Hive doesn't work at all.
|
|
warm-up-hive
|
|
run-step "Loading custom schemas" load-custom-schemas.log load-custom-schemas
|
|
# Run some steps in parallel, with run-step-backgroundable / run-step-wait-all.
|
|
# This is effective on steps that take a long time and don't depend on each
|
|
# other. Functional-query takes about ~35 minutes, and TPC-H and TPC-DS can
|
|
# finish while functional-query is running.
|
|
run-step-backgroundable "Loading functional-query data" load-functional-query.log \
|
|
load-data "functional-query" "exhaustive"
|
|
run-step-backgroundable "Loading TPC-H data" load-tpch.log load-data "tpch" "core"
|
|
run-step-backgroundable "Loading TPC-DS data" load-tpcds.log load-data "tpcds" "core"
|
|
run-step-wait-all
|
|
# Load tpch nested data.
|
|
# TODO: Hacky and introduces more complexity into the system, but it is expedient.
|
|
if [[ -n "$CM_HOST" ]]; then
|
|
LOAD_NESTED_ARGS="--cm-host $CM_HOST"
|
|
fi
|
|
run-step "Loading nested parquet data" load-nested.log \
|
|
${IMPALA_HOME}/testdata/bin/load_nested.py \
|
|
-t tpch_nested_parquet -f parquet/none ${LOAD_NESTED_ARGS:-}
|
|
run-step "Loading nested orc data" load-nested.log \
|
|
${IMPALA_HOME}/testdata/bin/load_nested.py \
|
|
-t tpch_nested_orc_def -f orc/def ${LOAD_NESTED_ARGS:-}
|
|
run-step "Loading auxiliary workloads" load-aux-workloads.log load-aux-workloads
|
|
run-step "Loading dependent tables" copy-and-load-dependent-tables.log \
|
|
copy-and-load-dependent-tables
|
|
run-step "Loading custom data" load-custom-data.log load-custom-data
|
|
run-step "Creating many block table" create-table-many-blocks.log \
|
|
${IMPALA_HOME}/testdata/bin/create-table-many-blocks.sh -p 1234 -b 1
|
|
elif [ "${TARGET_FILESYSTEM}" = "hdfs" ]; then
|
|
echo "Skipped loading the metadata."
|
|
run-step "Loading HBase data only" load-hbase-only.log \
|
|
load-data "functional-query" "core" "hbase/none"
|
|
fi
|
|
|
|
if [[ $SKIP_METADATA_LOAD -eq 1 ]]; then
|
|
# Tests depend on the kudu data being clean, so load the data from scratch.
|
|
# This is only necessary if this is not a full dataload, because a full dataload
|
|
# already loads Kudu functional and TPC-H tables from scratch.
|
|
run-step-backgroundable "Loading Kudu functional" load-kudu.log \
|
|
load-data "functional-query" "core" "kudu/none/none" force
|
|
run-step-backgroundable "Loading Kudu TPCH" load-kudu-tpch.log \
|
|
load-data "tpch" "core" "kudu/none/none" force
|
|
fi
|
|
run-step-backgroundable "Loading Hive UDFs" build-and-copy-hive-udfs.log \
|
|
build-and-copy-hive-udfs
|
|
run-step-wait-all
|
|
run-step "Running custom post-load steps" custom-post-load-steps.log \
|
|
custom-post-load-steps
|
|
|
|
if [ "${TARGET_FILESYSTEM}" = "hdfs" ]; then
|
|
# Caching tables in s3 returns an IllegalArgumentException, see IMPALA-1714
|
|
run-step "Caching test tables" cache-test-tables.log cache-test-tables
|
|
|
|
# TODO: Modify the .sql file that creates the table to take an alternative location into
|
|
# account.
|
|
run-step "Loading external data sources" load-ext-data-source.log \
|
|
copy-and-load-ext-data-source
|
|
|
|
run-step "Creating internal HBase table" create-internal-hbase-table.log \
|
|
create-internal-hbase-table
|
|
|
|
run-step "Checking HDFS health" check-hdfs-health.log check-hdfs-health
|
|
|
|
# Saving the list of created files can help in debugging missing files.
|
|
run-step "Logging created files" created-files.log hdfs dfs -ls -R /test-warehouse
|
|
fi
|
|
|
|
# TODO: Investigate why all stats are not preserved. Theoretically, we only need to
|
|
# recompute stats for HBase.
|
|
run-step "Computing table stats" compute-table-stats.log \
|
|
${IMPALA_HOME}/testdata/bin/compute-table-stats.sh
|
|
|
|
# IMPALA-8346: this step only applies if the cluster is the local minicluster
|
|
if [[ -z "$REMOTE_LOAD" ]]; then
|
|
run-step "Creating tpcds testcase data" create-tpcds-testcase-data.log \
|
|
${IMPALA_HOME}/testdata/bin/create-tpcds-testcase-files.sh
|
|
fi
|
|
|
|
if [[ $SKIP_RANGER -eq 0 ]]; then
|
|
run-step "Setting up Ranger" setup-ranger.log \
|
|
${IMPALA_HOME}/testdata/bin/setup-ranger.sh
|
|
fi
|
|
|
|
# Restart the minicluster. This is strictly to provide a sanity check that
|
|
# restarting the minicluster works and doesn't impact the tests. This is a common
|
|
# operation for developers, so it is nice to test it.
|
|
restart-cluster
|
|
|
|
# Kill the spawned timeout process and its child sleep process.
|
|
# There may not be a sleep process, so ignore failure.
|
|
pkill -P $TIMEOUT_PID || true
|
|
kill $TIMEOUT_PID
|