mirror of https://github.com/apache/cassandra
Merge branch 'cassandra-2.1' into trunk
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commit
7633d92058
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@ -52,12 +52,11 @@ table_definition: |
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#
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# If preceded by ~, the distribution is inverted
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#
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# Defaults for all columns are size: uniform(1..256), identity: uniform(1..1024)
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# Defaults for all columns are size: uniform(4..8), population: uniform(1..100B), cluster: fixed(1)
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#
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columnspec:
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- name: name
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clustering: uniform(1..100)
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size: uniform(1..4)
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- name: count
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population: fixed(1)
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@ -79,7 +78,3 @@ insert:
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queries:
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simple1: select * from counttest where name = ?
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#
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# In order to generate data consistently we need something to generate a unique key for this schema profile.
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#
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seed: changing this string changes the generated data. its hashcode is used as the random seed.
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@ -62,13 +62,12 @@ table_definition: |
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#
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# If preceded by ~, the distribution is inverted
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#
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# Defaults for all columns are size: uniform(1..256), identity: uniform(1..1024)
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# Defaults for all columns are size: uniform(4..8), population: uniform(1..100B), cluster: fixed(1)
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#
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columnspec:
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- name: name
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size: uniform(1..10)
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population: uniform(1..1M) # the range of unique values to select for the field (default is 100Billion)
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- name: choice
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- name: date
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cluster: uniform(1..4)
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- name: lval
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@ -92,8 +91,3 @@ insert:
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queries:
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simple1: select * from typestest where name = ? and choice = ? LIMIT 100
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range1: select * from typestest where name = ? and choice = ? and date >= ? LIMIT 100
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#
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# In order to generate data consistently we need something to generate a unique key for this schema profile.
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#
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seed: changing this string changes the generated data. its hashcode is used as the random seed.
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@ -64,26 +64,20 @@ table_definition: |
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#
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# If preceded by ~, the distribution is inverted
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#
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# Defaults for all columns are size: uniform(1..256), population: uniform(1..100B)
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# Defaults for all columns are size: uniform(4..8), population: uniform(1..100B), cluster: fixed(1)
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#
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columnspec:
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- name: name
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clustering: uniform(1..4)
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- name: date
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clustering: gaussian(1..20)
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cluster: gaussian(1..20)
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- name: lval
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population: fixed(1)
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- name: dates
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clustering: uniform(1..100)
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- name: inets
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clustering: uniform(1..200)
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- name: value
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insert:
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partitions: fixed(1) # number of unique partitions to update in a single operation
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# if perbatch < 1, multiple batches will be used but all partitions will
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# occur in all batches (unless already finished); only the row counts will vary
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pervisit: uniform(1..10)/100K # ratio of rows each partition should update in a single visit to the partition,
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pervisit: uniform(1..10)/10 # ratio of rows each partition should update in a single visit to the partition,
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# as a proportion of the total possible for the partition
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perbatch: fixed(1)/1 # number of rows each partition should update in a single batch statement,
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# as a proportion of the proportion we are inserting this visit
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@ -96,7 +90,3 @@ insert:
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queries:
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simple1: select * from insanitytest where name = ? and choice = ? LIMIT 100
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#
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# In order to generate data consistently we need something to generate a unique key for this schema profile.
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#
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seed: changing this string changes the generated data. its hashcode is used as the random seed.
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@ -111,7 +111,7 @@ public class StressProfile implements Serializable
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keyspaceCql = yaml.keyspace_definition;
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tableName = yaml.table;
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tableCql = yaml.table_definition;
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seedStr = yaml.seed;
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seedStr = "seed for stress";
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queries = yaml.queries;
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insert = yaml.insert;
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@ -140,21 +140,25 @@ public class StressProfile implements Serializable
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}
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columnConfigs = new HashMap<>();
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for (Map<String,Object> spec : yaml.columnspec)
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if (yaml.columnspec != null)
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{
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lowerCase(spec);
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String name = (String) spec.remove("name");
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DistributionFactory population = !spec.containsKey("population") ? null : OptionDistribution.get((String) spec.remove("population"));
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DistributionFactory size = !spec.containsKey("size") ? null : OptionDistribution.get((String) spec.remove("size"));
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DistributionFactory clustering = !spec.containsKey("cluster") ? null : OptionDistribution.get((String) spec.remove("cluster"));
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for (Map<String, Object> spec : yaml.columnspec)
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{
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lowerCase(spec);
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String name = (String) spec.remove("name");
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DistributionFactory population = !spec.containsKey("population") ? null : OptionDistribution.get((String) spec.remove("population"));
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DistributionFactory size = !spec.containsKey("size") ? null : OptionDistribution.get((String) spec.remove("size"));
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DistributionFactory clustering = !spec.containsKey("cluster") ? null : OptionDistribution.get((String) spec.remove("cluster"));
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if (!spec.isEmpty())
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throw new IllegalArgumentException("Unrecognised option(s) in column spec: " + spec);
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if (name == null)
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throw new IllegalArgumentException("Missing name argument in column spec");
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if (!spec.isEmpty())
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throw new IllegalArgumentException("Unrecognised option(s) in column spec: " + spec);
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if (name == null)
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throw new IllegalArgumentException("Missing name argument in column spec");
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GeneratorConfig config = new GeneratorConfig(yaml.seed + name, clustering, size, population);
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columnConfigs.put(name, config);
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GeneratorConfig config = new GeneratorConfig(seedStr + name, clustering, size, population);
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columnConfigs.put(name, config);
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}
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}
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}
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@ -25,7 +25,6 @@ import java.util.Map;
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public class StressYaml
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{
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public String seed;
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public String keyspace;
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public String keyspace_definition;
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public String table;
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