From fa710a586fdea33244bc10cc24a45f71bf88b87e Mon Sep 17 00:00:00 2001 From: satanson Date: Thu, 19 Sep 2024 15:03:42 +0800 Subject: [PATCH] [BugFix] Cached fragment misuses exogenous runtime filter Signed-off-by: satanson --- .../starrocks/planner/FragmentNormalizer.java | 10 ++-- .../com/starrocks/planner/PlanFragment.java | 53 ++++++++++--------- .../com/starrocks/qe/DefaultCoordinator.java | 10 ---- .../sql/plan/PlanFragmentBuilder.java | 2 + .../sql/plan/ReplayFromDumpTest.java | 16 ++++++ ...cache_misuse_exogenous_runtime_filter.json | 1 + 6 files changed, 52 insertions(+), 40 deletions(-) create mode 100644 fe/fe-core/src/test/resources/sql/query_dump/query_cache_misuse_exogenous_runtime_filter.json diff --git a/fe/fe-core/src/main/java/com/starrocks/planner/FragmentNormalizer.java b/fe/fe-core/src/main/java/com/starrocks/planner/FragmentNormalizer.java index 6c24290bb7a8a..aacaab126adf1 100644 --- a/fe/fe-core/src/main/java/com/starrocks/planner/FragmentNormalizer.java +++ b/fe/fe-core/src/main/java/com/starrocks/planner/FragmentNormalizer.java @@ -720,7 +720,7 @@ public boolean normalize() { // Get leftmost path List leftNodesTopDown = Lists.newArrayList(); for (PlanNode currNode = root; currNode != null && currNode.getFragment() == fragment; - currNode = currNode.getChild(0)) { + currNode = currNode.getChild(0)) { leftNodesTopDown.add(currNode); } @@ -774,15 +774,17 @@ public boolean normalize() { // Not cacheable unless alien GRF(s) take effects on this PlanFragment. // The alien GRF(s) mean the GRF(S) that not created by PlanNodes of the subtree rooted at // the PlanFragment.planRoot. + Set grfBuilders = fragment.getProbeRuntimeFilters().values().stream().filter(RuntimeFilterDescription::isHasRemoteTargets) .map(RuntimeFilterDescription::getBuildPlanNodeId).collect(Collectors.toSet()); if (!grfBuilders.isEmpty()) { List rightSiblings = Lists.newArrayList(); collectRightSiblingFragments(root, rightSiblings, Sets.newHashSet()); - Set acceptableGrfBuilders = rightSiblings.stream().flatMap( - frag -> frag.getBuildRuntimeFilters().values().stream().map( - RuntimeFilterDescription::getBuildPlanNodeId)).collect(Collectors.toSet()); + Set acceptableGrfBuilders = rightSiblings.stream() + .flatMap(frag -> frag.getBuildRuntimeFilters().values().stream()) + .map(RuntimeFilterDescription::getBuildPlanNodeId) + .collect(Collectors.toSet()); boolean hasAlienGrf = !Sets.difference(grfBuilders, acceptableGrfBuilders).isEmpty(); if (hasAlienGrf) { return false; diff --git a/fe/fe-core/src/main/java/com/starrocks/planner/PlanFragment.java b/fe/fe-core/src/main/java/com/starrocks/planner/PlanFragment.java index 69b8f78b459d2..aa8e15f4d9036 100644 --- a/fe/fe-core/src/main/java/com/starrocks/planner/PlanFragment.java +++ b/fe/fe-core/src/main/java/com/starrocks/planner/PlanFragment.java @@ -63,6 +63,7 @@ import java.nio.ByteBuffer; import java.util.ArrayList; +import java.util.Collections; import java.util.Comparator; import java.util.Deque; import java.util.LinkedList; @@ -71,6 +72,7 @@ import java.util.Queue; import java.util.Set; import java.util.function.Consumer; +import java.util.function.Function; import java.util.stream.Collectors; import java.util.stream.Stream; @@ -156,8 +158,8 @@ public class PlanFragment extends TreeNode { protected double fragmentCost; - protected final Map buildRuntimeFilters = Maps.newTreeMap(); - protected final Map probeRuntimeFilters = Maps.newTreeMap(); + protected Map buildRuntimeFilters = Maps.newHashMap(); + protected Map probeRuntimeFilters = Maps.newHashMap(); protected List> queryGlobalDicts = Lists.newArrayList(); protected Map queryGlobalDictExprs; @@ -704,34 +706,33 @@ public boolean isTransferQueryStatisticsWithEveryBatch() { return transferQueryStatisticsWithEveryBatch; } - public void collectBuildRuntimeFilters(PlanNode root) { - if (root instanceof ExchangeNode) { - return; - } - - if (root instanceof RuntimeFilterBuildNode) { - RuntimeFilterBuildNode rfBuildNode = (RuntimeFilterBuildNode) root; - for (RuntimeFilterDescription description : rfBuildNode.getBuildRuntimeFilters()) { - buildRuntimeFilters.put(description.getFilterId(), description); - } - } - - for (PlanNode node : root.getChildren()) { - collectBuildRuntimeFilters(node); - } + public void collectBuildRuntimeFilters() { + Map filters = Maps.newHashMap(); + collectNodes().stream() + .filter(node -> node instanceof RuntimeFilterBuildNode) + .flatMap(node -> ((RuntimeFilterBuildNode) node).getBuildRuntimeFilters().stream()) + .forEach(desc -> filters.put(desc.getFilterId(), desc)); + buildRuntimeFilters = filters; } - public void collectProbeRuntimeFilters(PlanNode root) { - for (RuntimeFilterDescription description : root.getProbeRuntimeFilters()) { - probeRuntimeFilters.put(description.getFilterId(), description); - } + public void collectProbeRuntimeFilters() { + Map filters = Maps.newHashMap(); + collectNodes().stream() + .flatMap(node -> node.getProbeRuntimeFilters().stream()) + .forEach(desc -> filters.put(desc.getFilterId(), desc)); + probeRuntimeFilters = filters; + } - if (root instanceof ExchangeNode) { - return; - } + public List collectNodes() { + List nodes = Lists.newArrayList(); + collectNodesImpl(getPlanRoot(), nodes); + return nodes; + } - for (PlanNode node : root.getChildren()) { - collectProbeRuntimeFilters(node); + private void collectNodesImpl(PlanNode root, List nodes) { + nodes.add(root); + if (!(root instanceof ExchangeNode)) { + root.getChildren().forEach(child -> collectNodesImpl(child, nodes)); } } diff --git a/fe/fe-core/src/main/java/com/starrocks/qe/DefaultCoordinator.java b/fe/fe-core/src/main/java/com/starrocks/qe/DefaultCoordinator.java index 2df0906165666..d04bdbab13d95 100644 --- a/fe/fe-core/src/main/java/com/starrocks/qe/DefaultCoordinator.java +++ b/fe/fe-core/src/main/java/com/starrocks/qe/DefaultCoordinator.java @@ -606,14 +606,6 @@ private void prepareResultSink() throws AnalysisException { setGlobalRuntimeFilterParams(rootExecFragment, worker.getBrpcIpAddress()); boolean isLoadType = !(rootExecFragment.getPlanFragment().getSink() instanceof ResultSink); if (isLoadType) { - // TODO (by satanson): Other DataSink except ResultSink can not support global - // runtime filter merging at present, we should support it in future. - // pipeline-level runtime filter needs to derive RuntimeFilterLayout, so we collect - // RuntimeFilterDescription - for (ExecutionFragment execFragment : executionDAG.getFragmentsInPreorder()) { - PlanFragment fragment = execFragment.getPlanFragment(); - fragment.collectBuildRuntimeFilters(fragment.getPlanRoot()); - } return; } @@ -769,8 +761,6 @@ private void setGlobalRuntimeFilterParams(ExecutionFragment topParams, for (ExecutionFragment execFragment : executionDAG.getFragmentsInPreorder()) { PlanFragment fragment = execFragment.getPlanFragment(); - fragment.collectBuildRuntimeFilters(fragment.getPlanRoot()); - fragment.collectProbeRuntimeFilters(fragment.getPlanRoot()); for (Map.Entry kv : fragment.getProbeRuntimeFilters().entrySet()) { List probeParamList = Lists.newArrayList(); for (final FragmentInstance instance : execFragment.getInstances()) { diff --git a/fe/fe-core/src/main/java/com/starrocks/sql/plan/PlanFragmentBuilder.java b/fe/fe-core/src/main/java/com/starrocks/sql/plan/PlanFragmentBuilder.java index 20a6fff10d70e..1ae3d9246a205 100644 --- a/fe/fe-core/src/main/java/com/starrocks/sql/plan/PlanFragmentBuilder.java +++ b/fe/fe-core/src/main/java/com/starrocks/sql/plan/PlanFragmentBuilder.java @@ -388,6 +388,8 @@ private static ExecPlan finalizeFragments(ExecPlan execPlan, TResultSinkType res } fragments.forEach(PlanFragment::removeDictMappingProbeRuntimeFilters); + fragments.forEach(PlanFragment::collectBuildRuntimeFilters); + fragments.forEach(PlanFragment::collectProbeRuntimeFilters); if (useQueryCache(execPlan)) { for (PlanFragment fragment : execPlan.getFragments()) { diff --git a/fe/fe-core/src/test/java/com/starrocks/sql/plan/ReplayFromDumpTest.java b/fe/fe-core/src/test/java/com/starrocks/sql/plan/ReplayFromDumpTest.java index 9df883b8dc9d9..a1e6add23340a 100644 --- a/fe/fe-core/src/test/java/com/starrocks/sql/plan/ReplayFromDumpTest.java +++ b/fe/fe-core/src/test/java/com/starrocks/sql/plan/ReplayFromDumpTest.java @@ -958,4 +958,20 @@ public void testQueryTimeout() { Assert.assertThrows(StarRocksPlannerException.class, () -> getPlanFragment(getDumpInfoFromFile("query_dump/query_timeout"), null, TExplainLevel.NORMAL)); } + + @Test + public void testQueryCacheMisuseExogenousRuntimeFilter() throws Exception { + String savedSv = connectContext.getSessionVariable().getJsonString(); + try { + connectContext.getSessionVariable().setEnableQueryCache(true); + QueryDumpInfo dumpInfo = + getDumpInfoFromJson(getDumpInfoFromFile("query_dump/query_cache_misuse_exogenous_runtime_filter")); + ExecPlan execPlan = UtFrameUtils.getPlanFragmentFromQueryDump(connectContext, dumpInfo); + Assert.assertTrue(execPlan.getFragments().stream().noneMatch(frag -> frag.getCacheParam() != null)); + Assert.assertTrue( + execPlan.getFragments().stream().anyMatch(frag -> !frag.getProbeRuntimeFilters().isEmpty())); + } finally { + connectContext.getSessionVariable().replayFromJson(savedSv); + } + } } diff --git a/fe/fe-core/src/test/resources/sql/query_dump/query_cache_misuse_exogenous_runtime_filter.json b/fe/fe-core/src/test/resources/sql/query_dump/query_cache_misuse_exogenous_runtime_filter.json new file mode 100644 index 0000000000000..f75abbfb3b7c1 --- /dev/null +++ b/fe/fe-core/src/test/resources/sql/query_dump/query_cache_misuse_exogenous_runtime_filter.json @@ -0,0 +1 @@ +{"statement":"SELECT tbl_mock_1985.mock_1981, (sum(tbl_mock_1991.mock_1984)) / 100 AS mock_1982, count(DISTINCT tbl_mock_1985.mock_002) AS mock_1983, tbl_mock_1985.mock_013\nFROM (SELECT min(tbl_mock_001.mock_024) AS mock_1981, tbl_mock_001.mock_002, tbl_mock_001.mock_013\nFROM db_mock_000.tbl_mock_001\nWHERE (((tbl_mock_001.mock_024 >= '2024-07-01') AND (tbl_mock_001.mock_030 = 'serverTrace')) AND (NOT ((get_json_string(tbl_mock_001.mock_052, '$.vipId')) LIKE 'coin%'))) AND ((get_json_string(tbl_mock_001.mock_052, '$.actionName')) = 'openUserVipSuccess')\nGROUP BY tbl_mock_001.mock_002, tbl_mock_001.mock_013) tbl_mock_1985 INNER JOIN[broadcast] (SELECT tbl_mock_001.mock_024, tbl_mock_001.mock_013, tbl_mock_001.mock_002, get_json_string(tbl_mock_001.mock_052, '$.price') AS mock_1984, get_json_string(tbl_mock_001.mock_052, '$.vipTimeType') AS mock_1987, get_json_string(tbl_mock_001.mock_052, '$.vipType') AS mock_1988, date(from_unixtime(round((floor(get_json_string(tbl_mock_001.mock_052, '$.vipGmtStart'))) / 1000, 0))) AS mock_1989, date(from_unixtime(round((floor(get_json_string(tbl_mock_001.mock_052, '$.vipGmtEnd'))) / 1000, 0))) AS mock_1990\nFROM db_mock_000.tbl_mock_001\nWHERE (((tbl_mock_001.mock_024 = '2024-07-01') AND (tbl_mock_001.mock_030 = 'serverTrace')) AND ((get_json_string(tbl_mock_001.mock_052, '$.actionName')) = 'openUserVipSuccess')) AND (NOT ((get_json_string(tbl_mock_001.mock_052, '$.vipId')) LIKE 'coin%'))) tbl_mock_1991 ON ((tbl_mock_1985.mock_002 = tbl_mock_1991.mock_002) AND (tbl_mock_1985.mock_1981 = tbl_mock_1991.mock_024)) AND (tbl_mock_1985.mock_013 = tbl_mock_1991.mock_013)\nGROUP BY tbl_mock_1985.mock_013, tbl_mock_1985.mock_1981","table_meta":{"db_mock_000.tbl_mock_001":"CREATE TABLE db_mock_000.tbl_mock_001 (\nmock_024 date ,\nmock_030 varchar(65533) ,\nmock_015 varchar(200) ,\nmock_016 varchar(200) ,\nmock_012 varchar(65533) ,\nmock_036 varchar(65533) ,\nmock_039 varchar(65533) ,\nmock_018 varchar(65533) ,\nmock_038 varchar(65533) ,\nmock_047 varchar(65533) ,\nmock_025 varchar(65533) ,\nmock_057 int(11) ,\nmock_058 int(11) ,\nmock_040 varchar(65533) ,\nmock_026 varchar(65533) ,\nmock_062 varchar(65533) ,\nmock_048 varchar(65533) ,\nmock_065 varchar(65533) ,\nmock_063 varchar(65533) ,\nmock_027 varchar(65533) ,\nmock_002 varchar(65533) ,\nmock_068 varchar(65533) ,\nmock_035 varchar(65533) ,\nmock_045 varchar(65533) ,\nmock_031 varchar(65533) ,\nmock_014 varchar(65533) ,\nmock_044 varchar(65533) ,\nmock_069 bigint(20) ,\nmock_003 varchar(65533) ,\nmock_056 varchar(65533) ,\nmock_029 double ,\nmock_023 varchar(65533) ,\nmock_028 double ,\nmock_019 varchar(65533) ,\nmock_042 bigint(20) ,\nmock_043 varchar(65533) ,\nmock_052 json ,\nmock_032 varchar(65533) ,\nmock_055 double ,\nmock_064 bigint(20) ,\nmock_022 varchar(65533) ,\nmock_017 varchar(65533) ,\nmock_009 varchar(65533) ,\nmock_006 varchar(65533) ,\nmock_007 varchar(65533) ,\nmock_008 varchar(65533) ,\nmock_054 varchar(65533) ,\nmock_041 varchar(65533) ,\nmock_013 varchar(65533) ,\nmock_051 varchar(65533) ,\nmock_037 int(11) ,\nmock_010 varchar(65533) ,\nmock_011 varchar(65533) ,\nmock_034 int(11) ,\nmock_061 varchar(65533) ,\nmock_060 datetime ,\nmock_033 varchar(65533) ,\nmock_059 varchar(65533) ,\nmock_049 varchar(65533) ,\nmock_066 varchar(65533) ,\nmock_053 varchar(65533) ,\nmock_067 date ,\nmock_050 varchar(65533) ,\nmock_004 varchar(65533) ,\nmock_005 varchar(65533) ,\nmock_021 int(11) ,\nmock_020 varchar(65533) ,\nmock_046 varchar(65533) \n) ENGINE= OLAP \nDUPLICATE KEY(mock_024, mock_030, mock_015)\nPARTITION BY RANGE(mock_024, mock_034)\n(PARTITION p2024070100 VALUES [(\"2024-07-01\", \"0\"), (\"2024-07-01\", \"1\")),\nPARTITION p2024070101 VALUES [(\"2024-07-01\", \"1\"), (\"2024-07-01\", \"2\")),\nPARTITION p2024070102 VALUES [(\"2024-07-01\", \"2\"), (\"2024-07-01\", \"3\")),\nPARTITION p2024070103 VALUES [(\"2024-07-01\", \"3\"), (\"2024-07-01\", \"4\")),\nPARTITION p2024070104 VALUES [(\"2024-07-01\", \"4\"), (\"2024-07-01\", \"5\")),\nPARTITION p2024070105 VALUES [(\"2024-07-01\", \"5\"), (\"2024-07-01\", \"6\")),\nPARTITION p2024070106 VALUES [(\"2024-07-01\", \"6\"), (\"2024-07-01\", \"7\")),\nPARTITION p2024070107 VALUES [(\"2024-07-01\", \"7\"), (\"2024-07-01\", \"8\")),\nPARTITION p2024070108 VALUES [(\"2024-07-01\", \"8\"), (\"2024-07-01\", \"9\")),\nPARTITION p2024070109 VALUES [(\"2024-07-01\", \"9\"), (\"2024-07-01\", \"10\")),\nPARTITION p2024070110 VALUES [(\"2024-07-01\", \"10\"), (\"2024-07-01\", \"11\")),\nPARTITION p2024070111 VALUES [(\"2024-07-01\", \"11\"), (\"2024-07-01\", \"12\")),\nPARTITION p2024070112 VALUES [(\"2024-07-01\", \"12\"), (\"2024-07-01\", \"13\")),\nPARTITION p2024070113 VALUES [(\"2024-07-01\", \"13\"), (\"2024-07-01\", \"14\")),\nPARTITION p2024070114 VALUES [(\"2024-07-01\", \"14\"), (\"2024-07-01\", \"15\")),\nPARTITION p2024070115 VALUES [(\"2024-07-01\", \"15\"), (\"2024-07-01\", \"16\")),\nPARTITION p2024070116 VALUES [(\"2024-07-01\", \"16\"), (\"2024-07-01\", \"17\")),\nPARTITION p2024070117 VALUES [(\"2024-07-01\", \"17\"), (\"2024-07-01\", \"18\")),\nPARTITION p2024070118 VALUES [(\"2024-07-01\", \"18\"), (\"2024-07-01\", \"19\")),\nPARTITION p2024070119 VALUES [(\"2024-07-01\", \"19\"), (\"2024-07-01\", \"20\")),\nPARTITION p2024070120 VALUES [(\"2024-07-01\", \"20\"), (\"2024-07-01\", \"21\")),\nPARTITION p2024070121 VALUES [(\"2024-07-01\", \"21\"), (\"2024-07-01\", \"22\")),\nPARTITION p2024070122 VALUES [(\"2024-07-01\", \"22\"), (\"2024-07-01\", \"23\")),\nPARTITION p2024070123 VALUES [(\"2024-07-01\", \"23\"), (\"2024-07-01\", \"24\")),\nPARTITION p2024070200 VALUES [(\"2024-07-02\", \"0\"), (\"2024-07-02\", \"1\")),\nPARTITION p2024070201 VALUES [(\"2024-07-02\", \"1\"), (\"2024-07-02\", \"2\")),\nPARTITION p2024070202 VALUES [(\"2024-07-02\", \"2\"), (\"2024-07-02\", \"3\")),\nPARTITION p2024070203 VALUES [(\"2024-07-02\", \"3\"), (\"2024-07-02\", \"4\")),\nPARTITION p2024070204 VALUES [(\"2024-07-02\", \"4\"), (\"2024-07-02\", \"5\")),\nPARTITION p2024070205 VALUES [(\"2024-07-02\", \"5\"), (\"2024-07-02\", \"6\")),\nPARTITION p2024070206 VALUES [(\"2024-07-02\", \"6\"), (\"2024-07-02\", \"7\")),\nPARTITION p2024070207 VALUES [(\"2024-07-02\", \"7\"), (\"2024-07-02\", \"8\")),\nPARTITION p2024070208 VALUES [(\"2024-07-02\", \"8\"), (\"2024-07-02\", \"9\")),\nPARTITION p2024070209 VALUES [(\"2024-07-02\", \"9\"), (\"2024-07-02\", \"10\")),\nPARTITION p2024070210 VALUES [(\"2024-07-02\", \"10\"), (\"2024-07-02\", \"11\")),\nPARTITION p2024070211 VALUES [(\"2024-07-02\", \"11\"), (\"2024-07-02\", \"12\")),\nPARTITION p2024070212 VALUES [(\"2024-07-02\", \"12\"), (\"2024-07-02\", \"13\")),\nPARTITION p2024070213 VALUES [(\"2024-07-02\", \"13\"), (\"2024-07-02\", \"14\")),\nPARTITION p2024070214 VALUES [(\"2024-07-02\", \"14\"), (\"2024-07-02\", \"15\")),\nPARTITION p2024070215 VALUES [(\"2024-07-02\", \"15\"), (\"2024-07-02\", \"16\")),\nPARTITION p2024070216 VALUES [(\"2024-07-02\", \"16\"), (\"2024-07-02\", \"17\")),\nPARTITION p2024070217 VALUES [(\"2024-07-02\", \"17\"), (\"2024-07-02\", \"18\")),\nPARTITION p2024070218 VALUES [(\"2024-07-02\", \"18\"), (\"2024-07-02\", \"19\")),\nPARTITION p2024070219 VALUES [(\"2024-07-02\", \"19\"), (\"2024-07-02\", \"20\")),\nPARTITION p2024070220 VALUES [(\"2024-07-02\", \"20\"), (\"2024-07-02\", \"21\")),\nPARTITION p2024070221 VALUES [(\"2024-07-02\", \"21\"), (\"2024-07-02\", \"22\")),\nPARTITION p2024070222 VALUES [(\"2024-07-02\", \"22\"), (\"2024-07-02\", \"23\")),\nPARTITION p2024070223 VALUES [(\"2024-07-02\", \"23\"), (\"2024-07-02\", \"24\")),\nPARTITION p2024070300 VALUES [(\"2024-07-03\", \"0\"), (\"2024-07-03\", \"1\")),\nPARTITION p2024070301 VALUES [(\"2024-07-03\", \"1\"), (\"2024-07-03\", \"2\")),\nPARTITION p2024070302 VALUES [(\"2024-07-03\", \"2\"), (\"2024-07-03\", \"3\")),\nPARTITION p2024070303 VALUES [(\"2024-07-03\", \"3\"), (\"2024-07-03\", \"4\")),\nPARTITION p2024070304 VALUES [(\"2024-07-03\", \"4\"), (\"2024-07-03\", \"5\")),\nPARTITION p2024070305 VALUES [(\"2024-07-03\", \"5\"), (\"2024-07-03\", \"6\")),\nPARTITION p2024070306 VALUES [(\"2024-07-03\", \"6\"), (\"2024-07-03\", \"7\")),\nPARTITION p2024070307 VALUES 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1.7265024E9, 0.0, 4.0, 89.0] ESTIMATE","mock_013":"[-Infinity, Infinity, 4.241385543044008E-6, 9.434632490149601, 5.0] ESTIMATE","mock_002":"[-Infinity, Infinity, 4.241385543044008E-6, 15.946243875912751, 187610.0] ESTIMATE","mock_030":"[-Infinity, Infinity, 4.241385543044008E-6, 9.245287577955752, 63.0] ESTIMATE","mock_052":"[-Infinity, Infinity, 0.0, 1024.0, 1.0] ESTIMATE"}},"explain_info":"PLAN FRAGMENT 0(F05)\n Output Exprs:69: min | 145: expr | 144: count | 49: mock_013\n Input Partition: UNPARTITIONED\n RESULT SINK\n\n 15:EXCHANGE\n cardinality: 250\n\nPLAN FRAGMENT 1(F04)\n\n Input Partition: HASH_PARTITIONED: 49: mock_013, 69: min\n OutPut Partition: UNPARTITIONED\n OutPut Exchange id: 15\n\n 14:Project\n | output columns:\n | 49 <-> [49: mock_013, VARCHAR, true]\n | 69 <-> [69: min, mock_024, true]\n | 144 <-> [144: count, BIGINT, false]\n | 145 <-> [143: sum, DOUBLE, true] / 100.0\n | cardinality: 250\n | column statistics: \n | * mock_013-->[-Infinity, Infinity, 0.0, 9.434632490149601, 5.0] ESTIMATE\n | * min-->[1.7197632E9, 1.7265024E9, 0.0, 4.0, 89.0] ESTIMATE\n | * count-->[0.0, 1319.4182999057855, 0.0, 8.0, 250.3125] ESTIMATE\n | * expr-->[-Infinity, Infinity, 0.0, 1.0, 1.0] UNKNOWN\n | \n 13:AGGREGATE (merge finalize)\n | aggregate: sum[([143: sum, DOUBLE, true]); args: DOUBLE; result: DOUBLE; args nullable: true; result nullable: true], count[([144: count, BIGINT, false]); args: VARCHAR; result: BIGINT; args nullable: true; result nullable: false]\n | group by: [49: mock_013, VARCHAR, true], [69: min, mock_024, true]\n | cardinality: 250\n | column statistics: \n | * mock_013-->[-Infinity, Infinity, 0.0, 9.434632490149601, 5.0] ESTIMATE\n | * min-->[1.7197632E9, 1.7265024E9, 0.0, 4.0, 89.0] ESTIMATE\n | * sum-->[-Infinity, Infinity, 0.0, 1.0, 1.0] UNKNOWN\n | * count-->[0.0, 1319.4182999057855, 0.0, 8.0, 250.3125] ESTIMATE\n | * expr-->[-Infinity, Infinity, 0.0, 1.0, 1.0] UNKNOWN\n | \n 12:EXCHANGE\n distribution mock_065: SHUFFLE\n partition exprs: [49: mock_013, VARCHAR, true], [69: min, mock_024, true]\n cardinality: 250\n\nPLAN FRAGMENT 2(F01)\n\n Input Partition: HASH_PARTITIONED: 21: mock_002, 49: mock_013\n OutPut Partition: HASH_PARTITIONED: 49: mock_013, 69: min\n OutPut Exchange id: 12\n\n 11:AGGREGATE (update serialize)\n | STREAMING\n | aggregate: sum[([143: sum, DOUBLE, true]); args: DOUBLE; result: DOUBLE; args nullable: true; result nullable: true], count[([21: mock_002, VARCHAR, true]); args: VARCHAR; result: BIGINT; args nullable: true; result nullable: false]\n | group by: [49: mock_013, VARCHAR, true], [69: min, mock_024, true]\n | cardinality: 250\n | column statistics: \n | * mock_013-->[-Infinity, Infinity, 0.0, 9.434632490149601, 5.0] ESTIMATE\n | * min-->[1.7197632E9, 1.7265024E9, 0.0, 4.0, 89.0] ESTIMATE\n | * sum-->[-Infinity, Infinity, 0.0, 1.0, 1.0] UNKNOWN\n | * count-->[0.0, 1319.4182999057855, 0.0, 8.0, 250.3125] ESTIMATE\n | \n 10:AGGREGATE (update serialize)\n | aggregate: sum[(cast([138: get_json_string, VARCHAR, true] as DOUBLE)); args: DOUBLE; result: DOUBLE; args nullable: true; result nullable: true]\n | group by: [49: mock_013, VARCHAR, true], [69: min, mock_024, true], [21: mock_002, VARCHAR, true]\n | cardinality: 1319\n | column statistics: \n | * mock_002-->[-Infinity, Infinity, 0.0, 15.946243875912751, 579.1685267076151] ESTIMATE\n | * mock_013-->[-Infinity, Infinity, 0.0, 9.434632490149601, 5.0] ESTIMATE\n | * min-->[1.7197632E9, 1.7265024E9, 0.0, 4.0, 89.0] ESTIMATE\n | * sum-->[-Infinity, Infinity, 0.0, 1.0, 1.0] UNKNOWN\n | \n 9:Project\n | output columns:\n | 21 <-> [21: mock_002, VARCHAR, true]\n | 49 <-> [49: mock_013, VARCHAR, true]\n | 69 <-> [69: min, mock_024, true]\n | 138 <-> [138: get_json_string, VARCHAR, true]\n | cardinality: 1319\n | column statistics: \n | * mock_002-->[-Infinity, Infinity, 0.0, 15.946243875912751, 579.1685267076151] ESTIMATE\n | * mock_013-->[-Infinity, Infinity, 0.0, 9.434632490149601, 5.0] ESTIMATE\n | * min-->[1.7197632E9, 1.7265024E9, 0.0, 4.0, 89.0] ESTIMATE\n | * get_json_string-->[-Infinity, Infinity, 0.0, 1.0, 1.0] UNKNOWN\n | \n 8:HASH JOIN\n | join op: INNER JOIN (BROADCAST)\n | equal join conjunct: [21: mock_002, VARCHAR, true] = [90: mock_002, VARCHAR, true]\n | equal join conjunct: [69: min, mock_024, true] = [70: mock_024, mock_024, true]\n | equal join conjunct: [49: mock_013, VARCHAR, true] = [118: mock_013, VARCHAR, true]\n | build runtime filters:\n | - filter_id = 0, build_expr = (90: mock_002), remote = true\n | - filter_id = 1, build_expr = (70: mock_024), remote = false\n | - filter_id = 2, build_expr = (118: mock_013), remote = true\n | output columns: 21, 49, 69, 138\n | can local shuffle: false\n | cardinality: 1319\n | column statistics: \n | * mock_002-->[-Infinity, Infinity, 0.0, 15.946243875912751, 579.1685267076151] ESTIMATE\n | * mock_013-->[-Infinity, Infinity, 0.0, 9.434632490149601, 5.0] ESTIMATE\n | * min-->[1.7197632E9, 1.7265024E9, 0.0, 4.0, 89.0] ESTIMATE\n | * mock_024-->[1.72512E9, 1.72512E9, 0.0, 4.0, 89.0] ESTIMATE\n | * mock_002-->[-Infinity, Infinity, 0.0, 15.946243875912751, 579.1685267076151] ESTIMATE\n | * mock_013-->[-Infinity, Infinity, 0.0, 9.434632490149601, 5.0] ESTIMATE\n | * get_json_string-->[-Infinity, Infinity, 0.0, 1.0, 1.0] UNKNOWN\n | \n |----7:EXCHANGE\n | distribution mock_065: BROADCAST\n | cardinality: 579\n | \n 4:AGGREGATE (merge finalize)\n | aggregate: min[([69: min, mock_024, true]); args: mock_024; result: mock_024; args nullable: true; result nullable: true]\n | group by: [21: mock_002, VARCHAR, true], [49: mock_013, VARCHAR, true]\n | having: 69: min IS NOT NULL\n | cardinality: 527653\n | probe runtime filters:\n | - filter_id = 1, probe_expr = (69: min)\n | column statistics: \n | * mock_002-->[-Infinity, Infinity, 0.0, 15.946243875912751, 187610.0] ESTIMATE\n | * mock_013-->[-Infinity, Infinity, 0.0, 9.434632490149601, 5.0] ESTIMATE\n | * min-->[1.7197632E9, 1.7265024E9, 0.0, 4.0, 89.0] ESTIMATE\n | \n 3:EXCHANGE\n distribution mock_065: SHUFFLE\n partition exprs: [21: mock_002, VARCHAR, true], [49: mock_013, VARCHAR, true]\n cardinality: 527653\n probe runtime filters:\n - filter_id = 0, probe_expr = (21: mock_002)\n - filter_id = 2, probe_expr = (49: mock_013)\n\nPLAN FRAGMENT 3(F02)\n\n Input Partition: RANDOM\n OutPut Partition: UNPARTITIONED\n OutPut Exchange id: 07\n\n 6:Project\n | output columns:\n | 70 <-> [70: mock_024, mock_024, true]\n | 90 <-> [90: mock_002, VARCHAR, true]\n | 118 <-> [118: mock_013, VARCHAR, true]\n | 138 <-> get_json_string[([106: mock_052, JSON, true], '$.mock_1984'); args: JSON,VARCHAR; result: VARCHAR; args nullable: true; result nullable: true]\n | cardinality: 579\n | column statistics: \n | * mock_024-->[1.72512E9, 1.72512E9, 0.0, 4.0, 89.0] ESTIMATE\n | * mock_002-->[-Infinity, Infinity, 0.0, 15.946243875912751, 579.1685267076151] ESTIMATE\n | * mock_013-->[-Infinity, Infinity, 0.0, 9.434632490149601, 5.0] ESTIMATE\n | * get_json_string-->[-Infinity, Infinity, 0.0, 1.0, 1.0] UNKNOWN\n | \n 5:OlapScanNode\n table: mock_001, rollup: mock_001\n preAggregation: on\n Predicates: 90: mock_002 IS NOT NULL, 70: mock_024 IS NOT NULL, 118: mock_013 IS NOT NULL, [70: mock_024, mock_024, true] = '2024-09-01', [71: mock_030, VARCHAR, true] = 'serverTrace', get_json_string[([106: mock_052, JSON, true], '$.actionName'); args: JSON,VARCHAR; result: VARCHAR; args nullable: true; result nullable: true] = 'openUserVipSuccess', NOT (get_json_string(106: mock_052, '$.vipId') LIKE 'coin%')\n partitionsRatio=24/2487, tabletsRatio=1152/1152\n tabletList=30170247,30170249,30170251,30170253,30170255,30170257,30170259,30170261,30170263,30170265 ...\n actualRows=4329919, avgRowSize=1063.6262\n cardinality: 579\n column statistics: \n * mock_024-->[1.72512E9, 1.72512E9, 0.0, 4.0, 89.0] ESTIMATE\n * mock_030-->[-Infinity, Infinity, 0.0, 9.245287577955752, 63.0] ESTIMATE\n * mock_002-->[-Infinity, Infinity, 0.0, 15.946243875912751, 579.1685267076151] ESTIMATE\n * mock_052-->[-Infinity, Infinity, 0.0, 1024.0, 1.0] ESTIMATE\n * mock_013-->[-Infinity, Infinity, 0.0, 9.434632490149601, 5.0] ESTIMATE\n * get_json_string-->[-Infinity, Infinity, 0.0, 1.0, 1.0] UNKNOWN\n\nPLAN FRAGMENT 4(F00)\n\n Input Partition: RANDOM\n OutPut Partition: HASH_PARTITIONED: 21: mock_002, 49: mock_013\n OutPut Exchange id: 03\n\n 2:AGGREGATE (update serialize)\n | STREAMING\n | aggregate: min[([1: mock_024, mock_024, true]); args: mock_024; result: mock_024; args nullable: true; result nullable: true]\n | group by: [21: mock_002, VARCHAR, true], [49: mock_013, VARCHAR, true]\n | cardinality: 527653\n | column statistics: \n | * mock_002-->[-Infinity, Infinity, 0.0, 15.946243875912751, 187610.0] ESTIMATE\n | * mock_013-->[-Infinity, Infinity, 0.0, 9.434632490149601, 5.0] ESTIMATE\n | * min-->[1.7197632E9, 1.7265024E9, 0.0, 4.0, 89.0] ESTIMATE\n | \n 1:Project\n | output columns:\n | 1 <-> [1: mock_024, mock_024, true]\n | 21 <-> [21: mock_002, VARCHAR, true]\n | 49 <-> [49: mock_013, VARCHAR, true]\n | cardinality: 1450639\n | column statistics: \n | * mock_024-->[1.7197632E9, 1.7265024E9, 0.0, 4.0, 89.0] ESTIMATE\n | * mock_002-->[-Infinity, Infinity, 0.0, 15.946243875912751, 187610.0] ESTIMATE\n | * mock_013-->[-Infinity, Infinity, 0.0, 9.434632490149601, 5.0] ESTIMATE\n | \n 0:OlapScanNode\n table: mock_001, rollup: mock_001\n preAggregation: on\n Predicates: 21: mock_002 IS NOT NULL, 49: mock_013 IS NOT NULL, [1: mock_024, mock_024, true] >= '2024-07-01', [2: mock_030, VARCHAR, true] = 'serverTrace', NOT (get_json_string(37: mock_052, '$.vipId') LIKE 'coin%'), get_json_string[([37: mock_052, JSON, true], '$.actionName'); args: JSON,VARCHAR; result: VARCHAR; args nullable: true; result nullable: true] = 'openUserVipSuccess'\n partitionsRatio=1911/2487, tabletsRatio=91728/91728\n tabletList=11764815,11764817,11764819,11764821,11764823,11764825,11764827,11764829,11764831,11764833 ...\n actualRows=161395086, avgRowSize=1062.6262\n cardinality: 1450639\n probe runtime filters:\n - filter_id = 0, probe_expr = (21: mock_002)\n - filter_id = 2, probe_expr = (49: mock_013)\n column statistics: \n * mock_024-->[1.7197632E9, 1.7265024E9, 0.0, 4.0, 89.0] ESTIMATE\n * mock_030-->[-Infinity, Infinity, 0.0, 9.245287577955752, 63.0] ESTIMATE\n * mock_002-->[-Infinity, Infinity, 0.0, 15.946243875912751, 187610.0] ESTIMATE\n * mock_052-->[-Infinity, Infinity, 0.0, 1024.0, 1.0] ESTIMATE\n * mock_013-->[-Infinity, Infinity, 0.0, 9.434632490149601, 5.0] ESTIMATE\n","session_variables":"{\"partial_update_mode\":\"auto\",\"cbo_cte_reuse\":false,\"character_set_connection\":\"utf8\",\"cbo_use_correlated_join_estimate\":true,\"enable_insert_strict\":true,\"enable_connector_adaptive_io_tasks\":true,\"tx_isolation\":\"REPEATABLE-READ\",\"enable_hive_metadata_cache_with_insert\":false,\"cbo_cte_reuse_rate_v2\":1.15,\"character_set_results\":\"utf8\",\"enable_iceberg_column_statistics\":true,\"materialized_view_union_rewrite_mode\":0,\"enable_count_star_optimization\":true,\"materialized_view_max_relation_mapping_size\":10,\"global_runtime_filter_build_min_size\":131072,\"enable_iceberg_identity_column_optimize\":true,\"query_excluding_mv_names\":\"\",\"enable_rewrite_simple_agg_to_meta_scan\":false,\"enable_adaptive_sink_dop\":true,\"consistent_hash_virtual_number\":128,\"enable_profile\":true,\"load_mem_limit\":0,\"cbo_eq_base_type\":\"varchar\",\"enable_materialized_view_for_insert\":false,\"large_decimal_underlying_type\":\"panic\",\"sql_safe_updates\":0,\"runtime_filter_early_return_selectivity\":0.05,\"enable_local_shuffle_agg\":true,\"disable_function_fold_constants\":false,\"enable_query_queue\":true,\"select_ratio_threshold\":0.15,\"query_delivery_timeout\":300,\"collation_database\":\"utf8_general_ci\",\"spill_mem_table_size\":104857600,\"follower_query_forward_mode\":\"\",\"orc_use_column_names\":false,\"cbo_use_lock_db\":false,\"new_planner_agg_stage\":0,\"enable_strict_order_by\":true,\"hash_join_interpolate_passthrough\":false,\"use_compute_nodes\":-1,\"collation_connection\":\"utf8_general_ci\",\"enable_rewrite_bitmap_union_to_bitamp_agg\":false,\"enable_force_rule_based_mv_rewrite\":false,\"enable_array_distinct_after_agg_opt\":true,\"resource_group\":\"\",\"enable_materialized_view_plan_cache\":true,\"spill_operator_max_bytes\":1048576000,\"cbo_max_reorder_node_use_dp\":10,\"enable_result_sink_accumulate\":true,\"enable_hive_column_stats\":true,\"enable_async_profile\":true,\"enable_groupby_use_output_alias\":false,\"global_runtime_filter_wait_timeout\":20,\"forward_to_leader\":false,\"count_distinct_column_buckets\":1024,\"cross_join_cost_penalty\":1000000,\"query_cache_agg_cardinality_limit\":5000000,\"enable_recapture_profile\":false,\"enable_pipeline_query_statistic\":true,\"cboPushDownAggregateMode_v1\":-1,\"window_partition_mode\":1,\"enable_deliver_batch_fragments\":true,\"enable_tablet_internal_parallel_v2\":true,\"interpolate_passthrough\":true,\"enable_incremental_mv\":false,\"cbo_push_down_topn_limit\":0,\"SQL_AUTO_IS_NULL\":false,\"event_scheduler\":\"OFF\",\"enable_tablet_scan_stat\":true,\"max_pipeline_dop\":64,\"broadcast_right_table_scale_factor\":10,\"materialized_view_rewrite_mode\":\"DEFAULT\",\"enable_simplify_case_when\":true,\"runtime_join_filter_push_down_limit\":1024000,\"big_query_log_cpu_second_threshold\":480,\"div_precision_increment\":4,\"runtime_adaptive_dop_max_block_rows_per_driver_seq\":16384,\"log_rejected_record_num\":0,\"cbo_push_down_distinct_below_window\":true,\"sql_mode_v2\":32,\"prefer_cte_rewrite\":false,\"optimizer_materialized_view_timelimit\":1000,\"hdfs_backend_selector_scan_range_shuffle\":false,\"pipeline_profile_level\":1,\"parallel_fragment_exec_instance_num\":8,\"max_scan_key_num\":-1,\"net_read_timeout\":60,\"streaming_preaggregation_mode\":\"auto\",\"hive_partition_stats_sample_size\":3000,\"enable_mv_planner\":false,\"enable_collect_table_level_scan_stats\":true,\"query_debug_options\":\"\",\"profile_timeout\":2,\"cbo_push_down_aggregate\":\"global\",\"spill_encode_level\":7,\"enable_query_dump\":false,\"global_runtime_filter_build_max_size\":67108864,\"enable_rewrite_sum_by_associative_rule\":true,\"query_cache_hot_partition_num\":3,\"enable_prune_complex_types\":true,\"query_cache_type\":0,\"max_parallel_scan_instance_num\":-1,\"query_cache_entry_max_rows\":409600,\"enable_mv_optimizer_trace_log\":false,\"connector_io_tasks_per_scan_operator\":16,\"enable_materialized_view_union_rewrite\":true,\"sql_quote_show_create\":true,\"scan_or_to_union_threshold\":50000000,\"enable_materialized_view_rewrite_partition_compensate\":true,\"enable_exchange_pass_through\":true,\"runtime_profile_report_interval\":10,\"query_cache_entry_max_bytes\":4194304,\"enable_partition_column_value_only_optimization\":true,\"enable_iceberg_ndv\":true,\"enable_exchange_perf\":false,\"workgroup_id\":0,\"enable_rewrite_groupingsets_to_union_all\":false,\"transmission_compression_type\":\"NO_COMPRESSION\",\"interactive_timeout\":3600,\"use_page_cache\":true,\"big_query_log_scan_bytes_threshold\":10737418240,\"collation_server\":\"utf8_general_ci\",\"cbo_decimal_cast_string_strict\":true,\"tablet_internal_parallel_mode\":\"auto\",\"enable_pipeline\":true,\"spill_mode\":\"auto\",\"enable_query_debug_trace\":false,\"like_predicate_consolidate_min\":2,\"cbo_materialized_view_rewrite_related_mvs_limit\":64,\"enable_show_all_variables\":false,\"full_sort_max_buffered_bytes\":16777216,\"wait_timeout\":1800,\"enable_query_tablet_affinity\":false,\"transmission_encode_level\":7,\"query_including_mv_names\":\"\",\"transaction_isolation\":\"REPEATABLE-READ\",\"enable_global_runtime_filter\":true,\"enable_load_profile\":true,\"enable_plan_validation\":true,\"load_transmission_compression_type\":\"NO_COMPRESSION\",\"global_runtime_filter_rpc_http_min_size\":67108864,\"cbo_materialized_view_rewrite_rule_output_limit\":3,\"cbo_enable_low_cardinality_optimize\":true,\"scan_use_query_mem_ratio\":0.3,\"new_planner_optimize_timeout\":30000,\"enable_outer_join_reorder\":true,\"force_schedule_local\":false,\"hudi_mor_force_jni_reader\":false,\"enable_agg_spill_preaggregation\":true,\"full_sort_late_materialization\":false,\"cbo_enable_greedy_join_reorder\":true,\"range_pruner_max_predicate\":100,\"enable_rbo_table_prune\":false,\"spillable_operator_mask\":-1,\"rpc_http_min_size\":2147482624,\"cbo_debug_alive_backend_number\":0,\"global_runtime_filter_probe_min_size\":102400,\"scan_or_to_union_limit\":4,\"enable_cbo_table_prune\":false,\"enable_parallel_merge\":true,\"cbo_materialized_view_rewrite_candidate_limit\":12,\"nested_mv_rewrite_max_level\":3,\"big_query_profile_threshold\":\"0s\",\"net_write_timeout\":60,\"cbo_prune_shuffle_column_rate\":0.1,\"enable_persistent_index_by_default\":true,\"hash_join_push_down_right_table\":true,\"pipeline_sink_dop\":0,\"broadcast_row_limit\":15000000,\"enable_populate_block_cache\":true,\"fragment_profile_drop_threshold_ms\":0,\"exec_mem_limit\":53687091200,\"enable_sort_aggregate\":false,\"query_cache_force_populate\":false,\"runtime_filter_on_exchange_node\":false,\"disable_join_reorder\":false,\"enable_rule_based_materialized_view_rewrite\":true,\"global_runtime_filter_rpc_timeout\":400,\"connector_scan_use_query_mem_ratio\":0.3,\"net_buffer_length\":16384,\"cbo_prune_subfield\":true,\"full_sort_max_buffered_rows\":1024000,\"query_timeout\":1200,\"connector_io_tasks_slow_io_latency_ms\":50,\"cbo_max_reorder_node\":50,\"enable_distinct_column_bucketization\":false,\"enable_big_query_log\":true,\"analyze_mv\":\"sample\",\"runtime_filter_scan_wait_time\":20,\"enable_sync_materialized_view_rewrite\":true,\"prefer_compute_node\":false,\"enable_strict_type\":false,\"enable_table_prune_on_update\":false,\"group_concat_max_len\":1024,\"parse_tokens_limit\":3500000,\"chunk_size\":4096,\"global_runtime_filter_probe_min_selectivity\":0.5,\"query_mem_limit\":0,\"enable_filter_unused_columns_in_scan_stage\":true,\"enable_scan_block_cache\":false,\"enable_materialized_view_single_table_view_delta_rewrite\":false,\"enable_prune_complex_types_in_unnest\":true,\"auto_increment_increment\":1,\"sql_dialect\":\"StarRocks\",\"big_query_log_scan_rows_threshold\":1000000000,\"character_set_client\":\"utf8\",\"autocommit\":true,\"enable_column_expr_predicate\":true,\"enable_runtime_adaptive_dop\":false,\"cbo_cte_max_limit\":10,\"storage_engine\":\"olap\",\"enable_optimizer_trace_log\":false,\"spill_operator_min_bytes\":10485760,\"cbo_enable_dp_join_reorder\":true,\"print_scan_operator_profile\":false,\"tx_visible_wait_timeout\":10,\"materialized_view_join_same_table_permutation_limit\":5,\"enable_materialized_view_view_delta_rewrite\":true,\"cbo_max_reorder_node_use_exhaustive\":4,\"enable_sql_digest\":false,\"spill_mem_table_num\":2,\"enable_spill\":false,\"enable_materialized_view_rewrite_greedy_mode\":false,\"pipeline_dop\":8,\"single_node_exec_plan\":false,\"join_implementation_mode_v2\":\"auto\",\"sql_select_limit\":9223372036854775807,\"enable_materialized_view_rewrite\":true,\"statistic_collect_parallel\":1,\"hdfs_backend_selector_hash_algorithm\":\"consistent\",\"enable_expr_prune_partition\":true,\"enable_topn_runtime_filter\":true,\"disable_colocate_join\":false,\"max_pushdown_conditions_per_column\":-1,\"default_table_compression\":\"lz4_frame\",\"runtime_adaptive_dop_max_output_amplification_factor\":0,\"skew_join_rand_range\":1000,\"choose_execute_instances_mode\":\"LOCALITY\",\"innodb_read_only\":true,\"spill_mem_limit_threshold\":0.8,\"cbo_reorder_threshold_use_exhaustive\":6,\"enable_predicate_reorder\":false,\"enable_query_cache\":true,\"transaction_read_only\":\"OFF\",\"max_allowed_packet\":33554432,\"time_zone\":\"Etc/UCT\",\"enable_multicolumn_global_runtime_filter\":false,\"character_set_server\":\"utf8\",\"cbo_use_nth_exec_plan\":0,\"io_tasks_per_scan_operator\":4,\"parallel_exchange_instance_num\":-1,\"enable_shared_scan\":false,\"cbo_derive_range_join_predicate\":false,\"allow_default_partition\":false,\"paimon_force_jni_reader\":false,\"enable_pipeline_level_shuffle\":true}","be_number":6,"be_core_stat":{"numOfHardwareCoresPerBe":"{\"10005\":32,\"10102\":32,\"10103\":32,\"10104\":32,\"10105\":32,\"10106\":32}","cachedAvgNumOfHardwareCores":-1},"exception":[],"version":"release/3.1.13-1.64","commit_version":"d5871c3"}