mirror of
https://github.com/featurebasedb/featurebase.git
synced 2026-09-05 16:15:56 +00:00
* expose Transaction on TranslateStore for DAX Snapshotting * try to fix ramdisk nonsense apparently, we were running in either a shell env or docker env randomly, so this could sometimes pass and sometimes fail since the shell env had the ramdisk set up and docker didn't. Now we force to run in docker always and set up ramdisk explicitly. * ramdisk mount should be defined on gitlab runner config now * debug ramdisk issue? * fix tests... and a buncha other stuff Took retry out of CI config because I think it's doing more harm than good at this point. The executor test I modified failed when I changed DefaultPartitionN to 8, but just because stuff was out of order so I made it more robust. I edited some data gen stuff to make shorter lines because it was making grep results unusable. the actual fix is in translate_boltdb_test.go * clean up, fix code review feedback |
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|---|---|---|
| .. | ||
| gen | ||
| testdata | ||
| all-field-types.go | ||
| bank.go | ||
| claim.go | ||
| cmd.go | ||
| common.go | ||
| custom.go | ||
| custom_test.go | ||
| customer.go | ||
| customer_segmentation.go | ||
| customer_segmentation_add_linkedin.go | ||
| customer_segmentation_test.go | ||
| datagen_test.go | ||
| dell.data.go | ||
| dell.go | ||
| dwarranty.go | ||
| equipment.data.go | ||
| equipment.go | ||
| example.go | ||
| hobbies.data.go | ||
| hughes.go | ||
| item.go | ||
| kitchen-sink-keyed.go | ||
| kitchen-sink.go | ||
| locations.data.go | ||
| merck.go | ||
| network.go | ||
| palo_alto.go | ||
| power_scenario.data.go | ||
| power_scenario_1.go | ||
| power_scenario_1_2.go | ||
| README.md | ||
| shared.go | ||
| sites.data.go | ||
| sites.go | ||
| sizing.go | ||
| skills.data.go | ||
| stringpk.go | ||
| texas_health.go | ||
| timeseries.go | ||
| titles.data.go | ||
| transactions.go | ||
| transactions_scenario_1.go | ||
| uscities.data.go | ||
| warranty.go | ||
| zip_codes.data.go | ||
Datagen Tool
Help Usage
Usage of datagen:
-c, --concurrency int Number of concurrent sources and indexing routines to launch. (default 1)
--dry-run Dry run - just flag parsing.
-e, --end-at uint ID at which to stop generating records.
--kafka.batch-size int Number of records to generate before sending them to Kafka all at once. Generally, larger means better throughput and more memory usage. (default 1000)
--kafka.hosts strings Comma separated list of host:port pairs for Kafka. (default [])
--kafka.registry-url string Location of Confluent Schema Registry. Must start with 'https://' if you want to use TLS.
--kafka.subject string Kafka schema subject.
--kafka.topic string Kafka topic to post to.
--pilosa.batch-size int Number of records to read before indexing all of them at once. Generally, larger means better throughput and more memory usage. 1,048,576 might be a good number.
--pilosa.cache-length uint Number of batches of ID mappings to cache. (default 64)
--pilosa.hosts strings Comma separated list of host:port pairs for Pilosa. (default [])
--pilosa.index string Name of Pilosa index.
--seed int Seed to use for any random number generation.
-s, --source string Source generator type. Running datagen with no arguments will list the available source types.
-b, --start-from uint ID at which to start generating records.
-t, --target string Destination for the generated data: [kafka, pilosa]. (default "pilosa")
--track-progress Periodically print status updates on how many records have been sourced.
Example Usage
The following command will create 100 records in Pilosa index (starting at ID 0 and ending at ID 99)
in the equipment index using the equipment data generator.
datagen --source=equipment --pilosa.index=equipment --end-at=99
Adding New Sources
TODO: redo README (or delete?)
If you're looking to add a new Source to datagen, the best thing to do is use the special "custom" datagen source (datagen --source=custom --custom-config=somefile.yaml) and write a somefile.yaml which describes the data you want to generate. An example can be found in datagen/testdata/custom.yaml, and there are some more in the molecula/technical-validation repo.