BigQuery language server
You can use bqls.nvim.
You can set Bigquery Project ID. If you don't specify it, gcloud config get project
will be used.
require("lspconfig").bqls.setup({
settings = {
project_id = "YOUR_PROJECT_ID",
},
})
You can change project_id with workspace/didChangeConfiguration
.
vim.lsp.get_clients({ name = "bqls" })[1].settings = { project_id="ANOTHER_PROJECT_ID" }
Execute a query and return the virtual text document url.
Request:
{
"command": "executeQuery",
"arguments": ["YOUR_DOCUMENT_URI"]
}
Response:
{
"textDocument": {
"uri": "bqls://project/${project}/job/${job}"
}
}
You can get the result of the query by requesting the bqls/virtualTextDocument
.
list up all datasets in the project.
Request:
{
"command": "listDatasets",
"arguments": ["YOUR_PROJECT_ID"]
}
Response:
{
"datasets": ["dataset1", "dataset2", "dataset3"]
}
list up all tables in the dataset.
Request:
{
"command": "listTables",
"arguments": ["YOUR_PROJECT_ID", "YOUR_DATASET_ID"]
}
Response:
{
"tables": ["table1", "table2", "table3"]
}
list up job histories in the project.
Arguments:
--all-user
: list up all jobs in the project. When this flag is not set, list up only jobs submitted by the user.
Request:
{
"command": "listJobHistories",
}
Response:
{
"jobs": [
{
"textDocument": { "uri": "bqls://..."},
"id": "job_id",
"owner": "[email protected]",
"summary": "job summary"
},
]
}
Requests a virtual text document from the LSP, which is a read only document that can be displayed in the client.
bqls
will encode all virtual files under custom schema bqls:
, so clients should route all requests for the bqls:
schema back to the bqls/virtualTextDocument
.
I used deno language server protocol below as reference.
For example, bqls can provide a virtual text document for a table information.
Currently, bqls://
schema supported the following path:
- table:
bqls://project/${project}/dataset/${dataset}/table/${table}
- job:
bqls://project/${project}/job/${job}
Requests:
interface VirtualTextDocumentParams {
textDocument: TextDocumentIdentifier;
}
Response:
interface VirtualTextDocument {
contents: MarkedString[];
result: QueryResult;
}
interface QueryResult {
columns: string[];
rows: any[][];
}