It's reasonable to allow "where x > 13" on decimal fields. Handle at least int64 and float64. Once this is up, we find that aggregates can return non-values, such as nil, in some cases; for instance, `percentile(x) where x > 13` can yield a nil if x is never greater than 13, rather than making up a value from zero data points. So we accept nil as a valid result type in PQL aggregates. As a result of this, change two tests which were unintentionally testing for an arcane edge case bug in which (1) we can't render a condition to PQL, such as because you specified an integer for a decimal field, and (2) the filter is using an aliased name, in which we would end up failing to generate a PQL filter, but *also* losing the SQL-layer filter, and produce wrong results as though there were no filter. We also alter the tests to use `o.price > 9`, because this lets us generate three user names, but only two distinct user names, so the test using DISTINCT returns a different value than the test not using DISTINCT, which helps us verify that it's actually working and not just lucky. As part of fixing that, there was an intermediate state where we rejected as an error any case where generating the PQL filter failed. This broke 21 more test cases, but in all of those cases, the SQL filter was actually working. ... But in two of them, we SHOULD have been able to generate PQL, because they were testing bools for null, which works fine. We just had a list of field types we allowed null tests against and omitted bool because I forgot that bool isn't always just treated as a kind of mutex. |
||
|---|---|---|
| .github/workflows | ||
| .gitlab | ||
| api/client | ||
| authn | ||
| authz | ||
| batch | ||
| buffer | ||
| bufferpool | ||
| cli | ||
| client | ||
| cmd | ||
| context | ||
| ctl | ||
| dax | ||
| debugstats | ||
| disco | ||
| encoding/proto | ||
| errors | ||
| etcd | ||
| extendiblehash | ||
| gcnotify | ||
| generator | ||
| gopsutil | ||
| hash | ||
| idk | ||
| install | ||
| internal | ||
| lattice | ||
| logger | ||
| lru | ||
| mock | ||
| monitor | ||
| net | ||
| pb | ||
| pql | ||
| prometheus | ||
| proto | ||
| qa | ||
| querycontext | ||
| rbf | ||
| roaring | ||
| runners | ||
| scripts | ||
| server | ||
| shardwidth | ||
| short_txkey | ||
| sql | ||
| sql3 | ||
| statik | ||
| stats | ||
| storage | ||
| systemlayer | ||
| syswrap | ||
| task | ||
| test | ||
| testdata | ||
| testhook | ||
| toml | ||
| tracing | ||
| txkey | ||
| vprint | ||
| wireprotocol | ||
| .gitignore | ||
| .golangci.yml | ||
| api.go | ||
| api_directive.go | ||
| api_directive_internal_test.go | ||
| api_directive_test.go | ||
| api_test.go | ||
| apimethod_string.go | ||
| apply.go | ||
| arrow.go | ||
| arrow_test.go | ||
| audit.go | ||
| audit_internal_test.go | ||
| audit_test.go | ||
| broadcast.go | ||
| bsi.go | ||
| bsi_test.go | ||
| cache.go | ||
| cache_test.go | ||
| catcher.go | ||
| cluster.go | ||
| cluster_internal_test.go | ||
| CODE_OF_CONDUCT.md | ||
| const_amd64.go | ||
| const_other.go | ||
| dataframe_test.go | ||
| dbshard.go | ||
| dbshard_internal_test.go | ||
| dbshard_test.go | ||
| delete_test.go | ||
| diagnostics.go | ||
| diagnostics_internal_test.go | ||
| doc.go | ||
| Dockerfile | ||
| Dockerfile-clustertests | ||
| Dockerfile-clustertests-client | ||
| Dockerfile-datagen | ||
| Dockerfile-dax | ||
| Dockerfile-dax-quick | ||
| Dockerfile-fbsql | ||
| et_test.go | ||
| event.go | ||
| executor.go | ||
| executor_internal_test.go | ||
| executor_test.go | ||
| field.go | ||
| field_internal_test.go | ||
| field_test.go | ||
| filesystem.go | ||
| fragment.go | ||
| fragment_internal_test.go | ||
| gc.go | ||
| gid.go | ||
| go.mod | ||
| go.sum | ||
| hack.go | ||
| handler.go | ||
| handler_test.go | ||
| holder.go | ||
| holder_internal_test.go | ||
| holder_test.go | ||
| http_handler.go | ||
| http_handler_internal_test.go | ||
| http_handler_test.go | ||
| http_translator.go | ||
| http_translator_test.go | ||
| idalloc.go | ||
| idalloc_test.go | ||
| importer.go | ||
| index.go | ||
| index_internal_test.go | ||
| index_test.go | ||
| internal_client.go | ||
| internal_client_test.go | ||
| iterator.go | ||
| iterator_internal_test.go | ||
| LICENSE | ||
| LICENSE-2.0.txt | ||
| license.exceptions | ||
| like.go | ||
| like_test.go | ||
| main_test.go | ||
| Makefile | ||
| metrics.go | ||
| nfpm.yaml | ||
| NOTICE | ||
| null_test.go | ||
| performancecounters.go | ||
| pilosa.go | ||
| pilosa_internal_test.go | ||
| pilosa_test.go | ||
| pprof.go | ||
| rbf.go | ||
| README.md | ||
| row.go | ||
| row_test.go | ||
| schema.go | ||
| serializer.go | ||
| server.go | ||
| server_internal_test.go | ||
| server_test.go | ||
| sql_test.go | ||
| stattx.go | ||
| systemlayer.go | ||
| time.go | ||
| time_internal_test.go | ||
| tracker.go | ||
| tracker_test.go | ||
| transaction.go | ||
| transaction_test.go | ||
| translate.go | ||
| translate_boltdb.go | ||
| translate_boltdb_internal_test.go | ||
| translate_boltdb_test.go | ||
| translator_test.go | ||
| tx.go | ||
| tx_internal_test.go | ||
| tx_test.go | ||
| txfactory.go | ||
| txfactory_internal_test.go | ||
| util.go | ||
| util_test.go | ||
| utils_internal_test.go | ||
| verchk.go | ||
| version.go | ||
| view.go | ||
| view_internal_test.go | ||
| wire_response.go | ||
FeatureBase
Pilosa is now FeatureBase
As of September 7, 2022, the Pilosa project is now FeatureBase. The core of the project remains the same: FeatureBase is the first real-time distributed database built entirely on bitmaps. (More information about updated capabilities and improvements below.)
FeatureBase delivers low-latency query results, regardless of throughput or query volumes, on fresh data with extreme efficiency. It works because bitmaps are faster, simpler, and far more I/O efficient than traditional column-oriented data formats. With FeatureBase, you can ingest data from batch data sources (e.g. S3, CSV, Snowflake, BigQuery, etc.) and/or streaming data sources (e.g. Kafka/Confluent, Kinesis, Pulsar).
For more information about FeatureBase, please visit www.featurebase.com.
Getting Started
Build FeatureBase Server from source
- Install go. Ensure that your shell's search path includes the go/bin directory.
- Clone the FeatureBase repository (or download as zip).
- In the featurebase directory, run
make installto compile the FeatureBase server binary. By default, it will be installed in the go/bin directory. - In the idk directory, run
make installto compile the ingester binaries. By default, they will be installed in the go/bin directory. - Run
featurebase server --handler.allowed-origins=http://localhost:3000to run FeatureBase server with default settings (learn more about configuring FeatureBase at the link below). The--handler.allowed-originsparameter allows the standalone web UI to talk to the server; this can be omitted if the web UI is not needed. - Run
curl localhost:10101/statusto verify the server is running and accessible.
Ingest Data and Query
- Run
molecula-consumer-csv \
--index repository \
--header "language__ID_F,project_id__ID_F" \
--id-field project_id \
--batch-size 1000 \
--files example.csv
This will ingest the example.csv file into a FeatureBase table called repository. If the table does not exist, it will be automatically created. Learn more about ingesting data into FeatureBase
- Query your data.
curl localhost:10101/index/repository/query \
-X POST \
-d 'Row(example=5)'
Learn about supported SQL, native Pilosa Query Language (PQL).
Data Model
Because FeatureBase is built on bitmaps, there is bit of a learning curve to grasp how your data is represented. Learn about Data Modeling.
More Information
Community
You can email us at community@featurebase.com or learn more about contributing at https://www.featurebase.com/community.
Chat with us: https://discord.gg/FBn2vEp7Na
What's Changed Since the Pilosa Days?
A lot has changed since the days of Pilosa. This list highlights some new capabilites included in FeatureBase. We have also made signficant improvements to the performance, scalability, and stability of the FeatureBase product.
- Query Languages: FeatureBase supports Pilosa Query Language (PQL), as well as SQL
- Stream and Batch Ingest: Combine real-time data streams with batch historical data and act on it within milliseconds.
- Mutable: Perform inserts, updates, and deletes at scale, in real time and on-the-fly. This is key for meeting data compliance requirements, and for reflecting the constantly-changing nature of high-volume data.
- Multi-Valued Set Fields: Store multiple comma-delimited values within a single field while increasing query performance of counts, TopKs, etc.
- Time Quantums: Setting a time quantum on a field creates extra views which allow ranged Row queries down to the time interval specified. For example, if the time quantum is set to YMD, ranged Row queries down to the granularity of a day are supported.
- RBF storage backend: this is a new compressed bitmap format which improves performance in a number of ways: ACID support on a per shard basis, prevents issues with the number of open files, reduces memory allocation and lock contention for reads, provides more consistent garbage collection, and allows backups to run concurrently with writes. However, because of this change, Pilosa backup files cannot be restored into FeatureBase.
License
FeatureBase is licensed under the Apache License, Version 2.0