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feat: new split_to_map udf #5563
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blueedgenick
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Jun 11, 2020
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532dd9c
initial commit new split_to_map udf
blueedgenick cadab2b
missed a 'final'
blueedgenick 62da1e8
fix checkstyle
blueedgenick 6381324
fix checkstyle
blueedgenick 2e24cc4
add new test-case from Almog's feedback. doc updates from Jim
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61 changes: 61 additions & 0 deletions
61
ksqldb-engine/src/main/java/io/confluent/ksql/function/udf/string/SplitToMap.java
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/* | ||
* Copyright 2020 Confluent Inc. | ||
* | ||
* Licensed under the Confluent Community License (the "License"; you may not use this file except | ||
* in compliance with the License. You may obtain a copy of the License at | ||
* | ||
* http://www.confluent.io/confluent-community-license | ||
* | ||
* Unless required by applicable law or agreed to in writing, software distributed under the License | ||
* is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OF ANY KIND, either express or implied. | ||
* See the License for the specific language governing permissions and limitations under the | ||
* License. | ||
*/ | ||
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package io.confluent.ksql.function.udf.string; | ||
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import com.google.common.base.Splitter; | ||
import io.confluent.ksql.function.udf.Udf; | ||
import io.confluent.ksql.function.udf.UdfDescription; | ||
import io.confluent.ksql.function.udf.UdfParameter; | ||
import java.util.Map; | ||
import java.util.stream.Collectors; | ||
import java.util.stream.StreamSupport; | ||
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@UdfDescription( | ||
name = "split_to_map", | ||
description = "Splits a string into key-value pairs and creates a map from them. The " | ||
+ "'entryDelimiter' splits the string into key-value pairs which are then split by " | ||
+ "'kvDelimiter'. If the same key is present multiple times in the input, the latest " | ||
+ "value for that key is returned. Returns NULL f the input text or either of the " | ||
+ "delimiters is NULL.") | ||
public class SplitToMap { | ||
@Udf | ||
public Map<String, String> splitToMap( | ||
@UdfParameter( | ||
description = "Separator string and values to join") final String input, | ||
@UdfParameter( | ||
description = "Separator string and values to join") final String entryDelimiter, | ||
@UdfParameter( | ||
description = "Separator string and values to join") final String kvDelimiter) { | ||
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if (input == null || entryDelimiter == null || kvDelimiter == null) { | ||
return null; | ||
} | ||
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if (entryDelimiter.isEmpty() || kvDelimiter.isEmpty() || entryDelimiter.equals(kvDelimiter)) { | ||
return null; | ||
} | ||
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final Iterable<String> entries = Splitter.on(entryDelimiter).omitEmptyStrings().split(input); | ||
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final Map<String, String> output = StreamSupport.stream(entries.spliterator(), false) | ||
.filter(e -> e.contains(kvDelimiter)) | ||
.map(kv -> Splitter.on(kvDelimiter).split(kv).iterator()) | ||
.collect(Collectors.toMap( | ||
kvIter -> kvIter.next(), | ||
kvIter -> kvIter.next(), | ||
(v1, v2) -> v2)); | ||
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return output; | ||
} | ||
} |
132 changes: 132 additions & 0 deletions
132
ksqldb-engine/src/test/java/io/confluent/ksql/function/udf/string/SplitToMapTest.java
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/* | ||
* Copyright 2018 Confluent Inc. | ||
* | ||
* Licensed under the Confluent Community License (the "License"); you may not use | ||
* this file except in compliance with the License. You may obtain a copy of the | ||
* License at | ||
* | ||
* http://www.confluent.io/confluent-community-license | ||
* | ||
* Unless required by applicable law or agreed to in writing, software | ||
* distributed under the License is distributed on an "AS IS" BASIS, WITHOUT | ||
* WARRANTIES OF ANY KIND, either express or implied. See the License for the | ||
* specific language governing permissions and limitations under the License. | ||
*/ | ||
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package io.confluent.ksql.function.udf.string; | ||
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import static org.hamcrest.MatcherAssert.assertThat; | ||
import static org.hamcrest.Matchers.equalTo; | ||
import static org.hamcrest.Matchers.hasEntry; | ||
import static org.hamcrest.Matchers.is; | ||
import static org.hamcrest.Matchers.nullValue; | ||
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import java.util.Collections; | ||
import java.util.Map; | ||
import org.junit.Test; | ||
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public class SplitToMapTest { | ||
There was a problem hiding this comment. Choose a reason for hiding this commentThe reason will be displayed to describe this comment to others. Learn more. can you add a test with whitespace? what do we want the behavior to be when there is whitespace (e.g. There was a problem hiding this comment. Choose a reason for hiding this commentThe reason will be displayed to describe this comment to others. Learn more. good idea, test added! |
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private static final SplitToMap udf = new SplitToMap(); | ||
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@Test | ||
public void shouldSplitStringByGivenDelimiterChars() { | ||
Map<String, String> result = udf.splitToMap("foo=apple;bar=cherry", ";", "="); | ||
assertThat(result, hasEntry("foo", "apple")); | ||
assertThat(result, hasEntry("bar", "cherry")); | ||
assertThat(result.size(), equalTo(2)); | ||
} | ||
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@Test | ||
public void shouldSplitStringGivenMultiCharDelimiters() { | ||
Map<String, String> result = udf.splitToMap("foo:=apple||bar:=cherry", "||", ":="); | ||
assertThat(result, hasEntry("foo", "apple")); | ||
assertThat(result, hasEntry("bar", "cherry")); | ||
assertThat(result.size(), equalTo(2)); | ||
} | ||
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@Test | ||
public void shouldSplitStringWithOnlyOneEntry() { | ||
Map<String, String> result = udf.splitToMap("foo=apple", ";", "="); | ||
assertThat(result, hasEntry("foo", "apple")); | ||
assertThat(result.size(), equalTo(1)); | ||
} | ||
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@Test | ||
public void shouldRetainWhitespacebetweenDelimiters() { | ||
Map<String, String> result = udf.splitToMap("foo :=\tapple || bar:=cherry", "||", ":="); | ||
assertThat(result, hasEntry("foo ", "\tapple ")); | ||
assertThat(result, hasEntry(" bar", "cherry")); | ||
assertThat(result.size(), equalTo(2)); | ||
} | ||
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@Test | ||
public void shouldDropEmptyEntriesFromSplit() { | ||
Map<String, String> result = udf.splitToMap("/foo:=apple//bar:=cherry/", "/", ":="); | ||
assertThat(result, hasEntry("foo", "apple")); | ||
assertThat(result, hasEntry("bar", "cherry")); | ||
assertThat(result.size(), equalTo(2)); | ||
} | ||
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@Test | ||
public void shouldDropEntriesWithoutKeyAndValue() { | ||
Map<String, String> result = udf.splitToMap("foo:=apple/cherry", "/", ":="); | ||
assertThat(result, hasEntry("foo", "apple")); | ||
assertThat(result.size(), equalTo(1)); | ||
} | ||
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@Test | ||
public void shouldReturnEmptyForInputWithoutDelimiters() { | ||
Map<String, String> result = udf.splitToMap("cherry", "/", ":="); | ||
assertThat(result, is(Collections.EMPTY_MAP)); | ||
} | ||
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@Test | ||
public void shouldReturnEmptyForEmptyInput() { | ||
Map<String, String> result = udf.splitToMap("", "/", ":="); | ||
assertThat(result, is(Collections.EMPTY_MAP)); | ||
} | ||
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@Test | ||
public void shouldKeepLatestValueForDuplicateKey() { | ||
Map<String, String> result = udf.splitToMap("/foo:=apple/foo:=cherry/", "/", ":="); | ||
assertThat(result, hasEntry("foo", "cherry")); | ||
assertThat(result.size(), equalTo(1)); | ||
} | ||
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@Test | ||
public void shouldReturnNullOnNullInputString() { | ||
Map<String, String> result = udf.splitToMap(null, "/", ":="); | ||
assertThat(result, is(nullValue())); | ||
} | ||
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@Test | ||
public void shouldReturnNullOnSameDelimiterChars() { | ||
Map<String, String> result = udf.splitToMap("foo:=apple/bar:=cherry", "/", "/"); | ||
assertThat(result, is(nullValue())); | ||
} | ||
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@Test | ||
public void shouldReturnNullOnEmptyEntryDelimiter() { | ||
Map<String, String> result = udf.splitToMap("foo:=apple/bar:=cherry", "", ":="); | ||
assertThat(result, is(nullValue())); | ||
} | ||
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@Test | ||
public void shouldReturnNullOnNullEntryDelimiter() { | ||
Map<String, String> result = udf.splitToMap("foo:=apple/bar:=cherry", null, ":="); | ||
assertThat(result, is(nullValue())); | ||
} | ||
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@Test | ||
public void shouldReturnNullOnEmptyValueDelimiter() { | ||
Map<String, String> result = udf.splitToMap("foo:=apple/bar:=cherry", "/", ""); | ||
assertThat(result, is(nullValue())); | ||
} | ||
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@Test | ||
public void shouldReturnNullOnNullValueDelimiter() { | ||
Map<String, String> result = udf.splitToMap("foo:=apple/bar:=cherry", "/", null); | ||
assertThat(result, is(nullValue())); | ||
} | ||
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} |
126 changes: 126 additions & 0 deletions
126
...test/resources/historical_plans/split-to-map_-_split_to_map/6.0.0_1591481024082/plan.json
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{ | ||
"plan" : [ { | ||
"@type" : "ksqlPlanV1", | ||
"statementText" : "CREATE STREAM INPUT (ID STRING KEY, INPUT STRING, ENTRYDELIM STRING, KVDELIM STRING) WITH (KAFKA_TOPIC='test_topic', VALUE_FORMAT='JSON');", | ||
"ddlCommand" : { | ||
"@type" : "createStreamV1", | ||
"sourceName" : "INPUT", | ||
"schema" : "`ID` STRING KEY, `INPUT` STRING, `ENTRYDELIM` STRING, `KVDELIM` STRING", | ||
"topicName" : "test_topic", | ||
"formats" : { | ||
"keyFormat" : { | ||
"format" : "KAFKA" | ||
}, | ||
"valueFormat" : { | ||
"format" : "JSON" | ||
} | ||
} | ||
} | ||
}, { | ||
"@type" : "ksqlPlanV1", | ||
"statementText" : "CREATE STREAM OUTPUT AS SELECT\n INPUT.ID ID,\n SPLIT_TO_MAP(INPUT.INPUT, INPUT.ENTRYDELIM, INPUT.KVDELIM) RESULT\nFROM INPUT INPUT\nEMIT CHANGES", | ||
"ddlCommand" : { | ||
"@type" : "createStreamV1", | ||
"sourceName" : "OUTPUT", | ||
"schema" : "`ID` STRING KEY, `RESULT` MAP<STRING, STRING>", | ||
"topicName" : "OUTPUT", | ||
"formats" : { | ||
"keyFormat" : { | ||
"format" : "KAFKA" | ||
}, | ||
"valueFormat" : { | ||
"format" : "JSON" | ||
} | ||
} | ||
}, | ||
"queryPlan" : { | ||
"sources" : [ "INPUT" ], | ||
"sink" : "OUTPUT", | ||
"physicalPlan" : { | ||
"@type" : "streamSinkV1", | ||
"properties" : { | ||
"queryContext" : "OUTPUT" | ||
}, | ||
"source" : { | ||
"@type" : "streamSelectV1", | ||
"properties" : { | ||
"queryContext" : "Project" | ||
}, | ||
"source" : { | ||
"@type" : "streamSourceV1", | ||
"properties" : { | ||
"queryContext" : "KsqlTopic/Source" | ||
}, | ||
"topicName" : "test_topic", | ||
"formats" : { | ||
"keyFormat" : { | ||
"format" : "KAFKA" | ||
}, | ||
"valueFormat" : { | ||
"format" : "JSON" | ||
} | ||
}, | ||
"sourceSchema" : "`ID` STRING KEY, `INPUT` STRING, `ENTRYDELIM` STRING, `KVDELIM` STRING" | ||
}, | ||
"keyColumnNames" : [ "ID" ], | ||
"selectExpressions" : [ "SPLIT_TO_MAP(INPUT, ENTRYDELIM, KVDELIM) AS RESULT" ] | ||
}, | ||
"formats" : { | ||
"keyFormat" : { | ||
"format" : "KAFKA" | ||
}, | ||
"valueFormat" : { | ||
"format" : "JSON" | ||
} | ||
}, | ||
"topicName" : "OUTPUT" | ||
}, | ||
"queryId" : "CSAS_OUTPUT_0" | ||
} | ||
} ], | ||
"configs" : { | ||
"ksql.extension.dir" : "ext", | ||
"ksql.streams.cache.max.bytes.buffering" : "0", | ||
"ksql.security.extension.class" : null, | ||
"ksql.transient.prefix" : "transient_", | ||
"ksql.persistence.wrap.single.values" : "true", | ||
"ksql.authorization.cache.expiry.time.secs" : "30", | ||
"ksql.schema.registry.url" : "", | ||
"ksql.streams.default.deserialization.exception.handler" : "io.confluent.ksql.errors.LogMetricAndContinueExceptionHandler", | ||
"ksql.output.topic.name.prefix" : "", | ||
"ksql.streams.auto.offset.reset" : "earliest", | ||
"ksql.query.pull.enable.standby.reads" : "false", | ||
"ksql.connect.url" : "http://localhost:8083", | ||
"ksql.service.id" : "some.ksql.service.id", | ||
"ksql.internal.topic.min.insync.replicas" : "1", | ||
"ksql.streams.shutdown.timeout.ms" : "300000", | ||
"ksql.internal.topic.replicas" : "1", | ||
"ksql.insert.into.values.enabled" : "true", | ||
"ksql.query.pull.max.allowed.offset.lag" : "9223372036854775807", | ||
"ksql.query.pull.max.qps" : "2147483647", | ||
"ksql.streams.default.production.exception.handler" : "io.confluent.ksql.errors.ProductionExceptionHandlerUtil$LogAndFailProductionExceptionHandler", | ||
"ksql.access.validator.enable" : "auto", | ||
"ksql.streams.bootstrap.servers" : "localhost:0", | ||
"ksql.streams.commit.interval.ms" : "2000", | ||
"ksql.metric.reporters" : "", | ||
"ksql.query.pull.metrics.enabled" : "false", | ||
"ksql.streams.auto.commit.interval.ms" : "0", | ||
"ksql.metrics.extension" : null, | ||
"ksql.streams.topology.optimization" : "all", | ||
"ksql.hidden.topics" : "_confluent.*,__confluent.*,_schemas,__consumer_offsets,__transaction_state,connect-configs,connect-offsets,connect-status,connect-statuses", | ||
"ksql.streams.num.stream.threads" : "4", | ||
"ksql.timestamp.throw.on.invalid" : "false", | ||
"ksql.authorization.cache.max.entries" : "10000", | ||
"ksql.metrics.tags.custom" : "", | ||
"ksql.pull.queries.enable" : "true", | ||
"ksql.udfs.enabled" : "true", | ||
"ksql.udf.enable.security.manager" : "true", | ||
"ksql.connect.worker.config" : "", | ||
"ksql.sink.window.change.log.additional.retention" : "1000000", | ||
"ksql.readonly.topics" : "_confluent.*,__confluent.*,_schemas,__consumer_offsets,__transaction_state,connect-configs,connect-offsets,connect-status,connect-statuses", | ||
"ksql.udf.collect.metrics" : "false", | ||
"ksql.persistent.prefix" : "query_", | ||
"ksql.query.persistent.active.limit" : "2147483647", | ||
"ksql.error.classifier.regex" : "" | ||
} | ||
} |
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We may also want to have
EncodeMap(map, entry_delim, kv_delim)
which encodes a map into a stringThere was a problem hiding this comment.
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i'll add it to my udf backlog ;) - although i'm less concerned about that from a use-case perspective as you can always construct almost-arbitrary json output by using structs/maps/arrays if you need that for a downstream system. The primary motivator for this one is when you get, for example, some encoded message from a mainframe MQ system that needs to be parsed out this way