* Clean up dax service interfaces
Rename some of the `computer` interfaces and organize them in the
appropriate files.
Remove `dax/computer/alpha` package
* Remove ComputeAPI (it was replaced by batch.Importer)
* add nss-tools dependecy to smoke test
* Fix formatting in CLI results with custom SQLResonse.UnmarshalJSON
When I started this, it was meant to be a quick fix to address the confusing
result formats we were seeing in the CLI. For example, all large integer values
were displayed in scientifc notation. This is because we were passing the result
types from JSON (in this case, float64) into pretty print. Similarly, `IDSets`
and `StringSets` where being printed using the default go Stringer for the types
[]int64 and []string respectively.
I started by writing a customer UnmarshalJSON() method for the `SQLResponse`
type. Part of this (the part which converts data types based on header types)
was already being used in dax tests, so this just formalizes that logic as part
of the `SQLResponse` type.
Then I realized that the sql3 tests (run against the `sql3` package) were
failing because sql3 is not actually returning the `IDSets` and `StringSets`
types. A future task is to formalize return types, define them, and modify sql3
to return them. Once that is done, we can remove the "typed" switch in the
`SQLResponse` json unmarshaller.
Another significant change is the modification to the `ExprDataType` interface:
```
type ExprDataType interface {
exprDataType()
TypeName() string
TypeDescription() string
TypeInfo() map[string]interface{}
}
```
I added two more methods in order to distinguish between a type (`DECIMAL`), its
description (`DECIMAL(2)`), and its type info (`"scale": int64(2)`). Currently,
the description can be used as the field definition in a CREATE TABLE statement,
but we may want to re-think that. Also, Decimal is the only type currently using
TypeInfo.
Finally, I tried to consilidate things around `dax.FieldType` instead of
comparing against parser types outside of sql3. We still have some sql3 parser
and planner types lurking about, but we can address those in future commits.
* Add some test coverage
* smoke test expected INT, now int
* minor fixes
* Introduce WireQueryResponse and related types
This also changes dax.FieldType to dax.BaseType.
* Populate WireQueryResponse correctly
Currently this is in the http handler, and in the queryer.
* Convert sql3 and dax tests to expect pilosa.WireQueryField in results
* fix PQL tests in the SQL defs
* Address a few of the skipped sql tests in dax
The idea behind this is to give AWS more information about what
instances we can let it actually instantitate, rather than have it be
one fixed instance type.
e.g., in this case, we are okay with any Graviton instance with at least
2 vCPU and 8 GiB memory.
The easist way to do that is to instead use a launch template, with
ec2_fleets or spot fleets.
I took out the part where we even support on-demand instances. This can
be readded later if it is necessary.
Apparently terraform can give us output saying that it succeded,
but give us an empty string for an IP address, which doesn't actually
let us use the IP address. Check for that case too in our overly
fancy setup.
This is a precursor to figuring out what's going wrong in a way
that lets us fix it more properly.
Also, request values, but don't instant-exit if they aren't present,
so we can actually do the retries.
switch perf-able to using same node type we use for other spot instances,
because otherwise it never finds any available capacity.
we switch the perf-able script to use the standard get_value function
instead of direct jq calls.
we try to grab server logs if the restore fails in the hopes of finding
out why the restore very occasionally fails.
We want to retry our terraform setup if it fails, so let's check whether
it worked and possibly retry.
This loop is awful because I'm trying to both check the exit status
and the reported IPs. Once I know whether the exit status predicts the
reported IPs that should go away.
This is a bit complicated and entangled, sorry.
First, we squash the auth-based smoke tests into the regular smoke
tests; we just run all the tests with auth on and that way we don't
need to spin up an entire separate cluster of machines just to run
a single query against them.
We improve the error detection, and standardize the jq-to-get-config
code. The purpose of this is to try to make sure that, if we actually
hit a failure and get "null" for a host name, we report *that*
as an error, rather than running ahead and producing 20+ separate
reports that ssh failed because it couldn't find a host named null.
Upgrade Go to 1.19
* Use go install to install statik for CI/CD
* Switch from stretch to buster for idk
The stretch release doesn't exist anymore for go 1.19 docker images.
buster is a newer version of Debian anyway (v10 vs v9)
Co-authored-by: Fletcher Haynes <fletcher.haynes@molecula.com>
* unifying idk and featurebase: first pass
* resolved conflict with master for gitignore & dockerignore
* deleted binaries that were accidentally pushed to git
* combined gitlab jobs for idk & featurebase
* run go fmt for idk
* updated ssh env variable, and made docker password variable in gitlab env variables
* fixed typo assigning variable name
* trying to fix docker login error
* trying a different solution for docker password
* pass registry
* fixed docker login
* updated paths for idk
* exclude idk tests from featurebase test run
* fix vendor error
* update certificates
* grpc needs to be in version 1.38
genproto, which is imported by big query updates the grpc version to 1.47.0
grpc 1.47.0 causes etcd to deadlock when calling etcd.Close()
the fix is to have a replace in go.mod to specify a specific grpc version
* run go mod tidy
* go mod
* run go mod tidy
* exclude bigquery since it is causing issues and undo grpc replace in go.mod
* fix grpc version
* fix formatting error
* update formatting
* attempt to fix formatting
* update path for code coverage
* update to use current branch binaries, not master
* fix for building idk - path updates
* udpate path for binaries
* update job dependecies
* update docker idk tests to use the current branch registry
* update stages for jobs
* updated job dependencies
* not allow idk s3 dump to fail since it is a dependency for integration tests
* update dependecy for idk tests
* update paths for idk build and code coverage
* download featurebase binary from s3
* pass branch name to all setup scripts
* change to current branch instead of master
* updated sonarcloud
* sonarcloud fix and branch name fix
* trying to speed up pipeline run time
* update stage
* branch name fix + sonar cloud
* sonarcloud
* spot instance test
* update outputs.tf to provide spot instances
* uptate outputs.tf data_node_ips
* propogate spot instance request tags to the instances
This adds a shard-based import endpoint which takes bitmap data for
all field types and imports data for the whole shard transactionally.
It uses the BitmapRewriter interface to try to intelligently allow for
setting and clearing bits simultaneously without multiple writes which
is especially helpful when ingesting into int-like fields, but also
allows clear-and-then-set behavior for set fields.
* Use IP whitelisting for ingest
For ingest, use configured IPs to authenticate the requests.
Auth-token will no longer be used for requests from ingest consumers.
If IP in request is in configured IPs, authenticate and authorize as an admin.
If IP in request is not in configured IPs, proceed with the standard authentication/authorization using ADD.
* need to remove port from client IP
* addressed review comments
- terraform scripts to set up cluster
- cloud-formation scripts to set up cluster
- set up ingest node with kafka server and datagen
- set up second ingest node with molecula-consumer-kafka-static
- set up datadog in all nodes (ingest + featurebase)
- set up script to execute different queries
- only run delete test on schedule
When you backup a cluster, we call /schema which marshals timestamp field options to
json, and restores the fields with those options. If the min and max are missing,
they are set to 0 on restore, which causes an issue on subsequent ingest.
Fixes [SUP-213](https://molecula.atlassian.net/browse/SUP-213) and
[FB-1332](https://molecula.atlassian.net/browse/FB-1332)
this stems from https://molecula.atlassian.net/browse/SUP-194 where the string
"standard" was being passed to viewTimePart, which output "standard" as the result.
this is not a valid time string and was causing confusing errors. now it simply
doesn't do that
this commit also adds regression testing framework and a regression test for fb-1287
