Package org.apache.cassandra.stress.generate.values

Examples of org.apache.cassandra.stress.generate.values.Generator.generate()

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        for (int i = 0 ; i < partitionKey.length ; i++)
        {
            Generator generator = this.generator.partitionKey.get(i);
            // set the partition key seed based on the current work item we're processing
            generator.setSeed(seed.seed);
            Object key = generator.generate();
            partitionKey[i] = key;
            // then contribute this value to the data seed
            idseed = seed(key, generator.type, idseed);
        }
        this.seed = seed;
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                return Collections.emptyList();
            for (int i = 0 ; i < row.row.length ; i++)
            {
                Generator gen = generator.valueComponents.get(i);
                gen.setSeed(idseed);
                row.row[i] = gen.generate();
            }
            done = true;
            return Collections.singleton(row);
        }
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            // and then fill the row with the _non-clustering_ values for the position we _were_ at, as this is what we'll deliver
            for (int i = clusteringSeeds.length ; i < row.row.length ; i++)
            {
                Generator gen = generator.valueComponents.get(i - clusteringSeeds.length);
                gen.setSeed(rowSeed);
                row.row[i] = gen.generate();
            }
            returnedOne = true;
            forceReturnOne = false;

            // then we advance the leaf level
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        for (int i = 0 ; i < partitionKey.length ; i++)
        {
            Generator generator = this.generator.partitionKey.get(i);
            // set the partition key seed based on the current work item we're processing
            generator.setSeed(seed);
            Object key = generator.generate();
            partitionKey[i] = key;
            // then contribute this value to the data seed
            idseed = seed(key, generator.type, idseed);
        }
        this.idseed = idseed;
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                return Collections.emptyList();
            for (int i = 0 ; i < row.row.length ; i++)
            {
                Generator gen = generator.valueComponents.get(i);
                gen.setSeed(idseed);
                row.row[i] = gen.generate();
            }
            done = true;
            return Collections.singleton(row);
        }
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            {
                Generator gen = generator.valueComponents.get(i - clusteringSeeds.length);
                long seed = clusteringSeeds[depth];
                seed = seed(clusteringComponents[depth].peek(), generator.clusteringComponents.get(depth).type, seed);
                gen.setSeed(seed);
                row.row[i] = gen.generate();
            }
            clusteringComponents[depth].poll();

            return advance(depth, continueChance);
        }
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        for (int i = 0 ; i < partitionKey.length ; i++)
        {
            Generator generator = this.generator.partitionKey.get(i);
            // set the partition key seed based on the current work item we're processing
            generator.setSeed(seed);
            Object key = generator.generate();
            partitionKey[i] = key;
            // then contribute this value to the data seed
            idseed = seed(key, generator.type, idseed);
        }
        this.idseed = idseed;
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                return Collections.emptyList();
            for (int i = 0 ; i < row.row.length ; i++)
            {
                Generator gen = generator.valueComponents.get(i);
                gen.setSeed(idseed);
                row.row[i] = gen.generate();
            }
            done = true;
            return Collections.singleton(row);
        }
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            {
                Generator gen = generator.valueComponents.get(i - clusteringSeeds.length);
                long seed = clusteringSeeds[depth];
                seed = seed(clusteringComponents[depth].peek(), generator.clusteringComponents.get(depth).type, seed);
                gen.setSeed(seed);
                row.row[i] = gen.generate();
            }
            clusteringComponents[depth].poll();

            return advance(depth, continueChance);
        }
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