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new 11acd5f edit docs
11acd5f is described below
commit 11acd5faa756a1b1be0519fc6335116d0ec793fb
Author: Bridget Bevens <[email protected]>
AuthorDate: Thu May 30 20:05:51 2019 -0700
edit docs
---
.../011-running-drill-on-docker.md | 15 ++++++---------
.../025-optimizing-parquet-reading.md | 4 ++--
_docs/sql-reference/sql-commands/009-analyze-table.md | 19 ++++++++++---------
.../sql-commands/011-refresh-table-metadata.md | 4 ++--
_docs/sql-reference/sql-commands/021-create-schema.md | 6 ++++--
5 files changed, 24 insertions(+), 24 deletions(-)
diff --git
a/_docs/install/installing-drill-in-embedded-mode/011-running-drill-on-docker.md
b/_docs/install/installing-drill-in-embedded-mode/011-running-drill-on-docker.md
index f3e49b2..c1c9de0 100644
---
a/_docs/install/installing-drill-in-embedded-mode/011-running-drill-on-docker.md
+++
b/_docs/install/installing-drill-in-embedded-mode/011-running-drill-on-docker.md
@@ -1,6 +1,6 @@
---
title: "Running Drill on Docker"
-date: 2019-05-24
+date: 2019-05-31
parent: "Installing Drill in Embedded Mode"
---
@@ -10,19 +10,16 @@ Currently, you can only run Drill in embedded mode in a
Docker container. Embedd
## Prerequisite
-You must have the Docker client (version 18 or later) installed on your
machine.
+You must have the Docker client (version 18 or later) [installed on your
machine](https://docs.docker.com/install/).
-- [Docker for Mac](https://www.docker.com/docker-mac)
-- [Docker for Windows](https://www.docker.com/docker-windows)
-- [Docker for Oracle Linux](https://www.docker.com/docker-oracle-linux)
## Running Drill in a Docker Container
-You can start and run a Docker container in “detached” mode or “foreground”
mode. Foreground is the default mode. Foreground mode runs the Drill process in
the container and attaches the console to Drill’s standard input, output, and
standard error. Detached mode runs the container in the background.
+You can start and run a Docker container in detached mode or foreground mode.
[Detached
mode]({{site.baseurl}}/docs/running-drill-on-docker/#running-the-drill-docker-container-in-detached-mode)
runs the container in the background. Foreground is the default mode.
[Foreground
mode]({{site.baseurl}}/docs/running-drill-on-docker/#running-the-drill-docker-container-in-foreground-mode)
runs the Drill process in the container and attaches the console to Drill’s
standard input, output, and stan [...]
-Whether you run the Docker container in detached or foreground mode, you start
Drill in a container by issuing the docker run command with some options.
+Whether you run the Docker container in detached or foreground mode, you start
Drill in a container by issuing the docker `run` command with some options, as
described in the following table:
-The following table describes the options:
+
| Option | Description
|
|------------------------------|--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
@@ -55,7 +52,7 @@ At the prompt, you can enter the following simple query to
verify that Drill is
Open a terminal window (Command Prompt or PowerShell, but not PowerShell ISE)
and then issue the following commands and options to connect to SQLLine (the
Drill shell):
-**Note:** When you run the Drill Docker container in Detached mode, you
connect to SQLLine (the Drill shell) using drill-localhost.
+**Note:** When you run the Drill Docker container in detached mode, you
connect to SQLLine (the Drill shell) using drill-localhost.
$ docker run -i --name drill-1.16.0 -p 8047:8047 --detach -t
drill/apache-drill:1.16.0 /bin/bash
<displays container ID>
diff --git a/_docs/performance-tuning/025-optimizing-parquet-reading.md
b/_docs/performance-tuning/025-optimizing-parquet-reading.md
index 65884af..a37fc53 100644
--- a/_docs/performance-tuning/025-optimizing-parquet-reading.md
+++ b/_docs/performance-tuning/025-optimizing-parquet-reading.md
@@ -1,11 +1,11 @@
---
title: "Optimizing Parquet Metadata Reading"
-date: 2017-08-10 22:24:37 UTC
+date: 2019-05-31
parent: "Performance Tuning"
---
Parquet metadata caching is a feature that enables Drill to read a single
metadata cache file instead of retrieving metadata from multiple Parquet files
during the query-planning phase.
-Parquet metadata caching is available for Parquet data in Drill 1.2 and later.
To enable Parquet metadata caching, issue the REFRESH TABLE METADATA <path to
table> command. When you run this command Drill generates a metadata cache
file.
+Parquet metadata caching is available for Parquet data in Drill 1.2 and later.
To enable Parquet metadata caching, issue the [REFRESH TABLE
METADATA]({{site.baseurl}}/docs/refresh-table-metadata/) <path to table>
command. When you run this command Drill generates a metadata cache file.
{% include startnote.html %}Parquet metadata caching does not benefit queries
on Hive tables, HBase tables, or text files.{% include endnote.html %}
diff --git a/_docs/sql-reference/sql-commands/009-analyze-table.md
b/_docs/sql-reference/sql-commands/009-analyze-table.md
index 544f4a9..9251d0e 100644
--- a/_docs/sql-reference/sql-commands/009-analyze-table.md
+++ b/_docs/sql-reference/sql-commands/009-analyze-table.md
@@ -1,16 +1,17 @@
---
title: "ANALYZE TABLE"
-date: 2019-05-02
+date: 2019-05-31
parent: "SQL Commands"
---
-Drill 1.16 and later supports the ANALYZE TABLE statement. The ANALYZE TABLE
statement computes statistics on Parquet data stored in tables and directories.
ANALYZE TABLE writes statistics to a JSON file in the `.stats.drill` directory,
for example `/user/table1/.stats.drill/0_0.json`. The optimizer in Drill uses
these statistics to estimate filter, aggregation, and join cardinalities and
create more efficient query plans.
+Drill 1.16 and later supports the ANALYZE TABLE statement. The ANALYZE TABLE
statement computes statistics on Parquet data stored in tables and directories.
The optimizer in Drill uses statistics to estimate filter, aggregation, and
join cardinalities and create an optimal query plan.
+ANALYZE TABLE writes statistics to a JSON file in the `.stats.drill`
directory, for example `/user/table1/.stats.drill/0_0.json`.
-You can run the ANALYZE TABLE statement to calculate statistics for tables,
columns, and directories with Parquet data; however, Drill will not use the
statistics for query planning unless you enable the `planner.statistics.use`
option, as shown:
+Drill will not use the statistics for query planning unless you enable the
`planner.statistics.use` option, as shown:
SET `planner.statistics.use` = true;
-Alternatively, you can enable the option in the Drill Web UI at
`http://<drill-hostname-or-ip>:8047/options`.
+Alternatively, you can enable the option in the Drill Web UI at
`http://<drill-hostname-or-ip-address>:8047/options`.
## Syntax
@@ -41,15 +42,15 @@ An integer that specifies the percentage of data on which
to compute statistics.
## Related Command
-If you drop a table on which you have run ANALYZE TABLE, the statistics are
automatically removed with the table:
+If you drop a table that you have already run ANALYZE TABLE against, the
statistics are automatically removed with the table:
DROP TABLE [IF EXISTS] [workspace.]name
-If you want to remove statistics for a table (and keep the table), you must
remove the directory in which Drill stores the statistics:
+To remove statistics for a table you want to keep, you must remove the
directory in which Drill stores the statistics:
DROP TABLE [IF EXISTS] [workspace.]name/.stats.drill
-If you have already issued the ANALYZE TABLE statement against specific
columns, a table, or directory, you must run the DROP TABLE statement with
`/.stats.drill` before you can successfully run the ANALYZE TABLE statement
against the data source again, for example:
+If you have already issued the ANALYZE TABLE statement against specific
columns, table, or directory, you must run the DROP TABLE statement with
`/.stats.drill` before you can successfully run the ANALYZE TABLE statement
against the data source again, for example:
DROP TABLE `table_stats/Tpch0.01/parquet/customer/.stats.drill`;
@@ -146,10 +147,10 @@ For the predicate `"WHERE a = 5"`, in the example
histogram above, you can see t
Next, consider the range predicate `"WHERE a > 5 AND a <= 16"`. The range
spans part of bucket [1, 7] and entire buckets [8, 9], [10, 11] and [12, 16].
The total estimate = (7-5)/7 * 16 + 16 + 16 + 16 = 53 (approximately). The
actual count is 59.
-**Viewing Histogram Statistics for a Column**
+**Viewing Histogram Statistics for a Column**
Histogram statistics are generated for each column, as shown:
-qhistogram":{"category":"numeric-equi-depth","numRowsPerBucket":150,"buckets":[0.0,2.0,4.0,7.0,9.0,12.0,15.199999999999978,17.0,19.0,22.0,24.0]
+
qhistogram":{"category":"numeric-equi-depth","numRowsPerBucket":150,"buckets":[0.0,2.0,4.0,7.0,9.0,12.0,15.199999999999978,17.0,19.0,22.0,24.0]
In this example, there are 10 buckets. Each bucket contains 150 rows, which is
calculated as the number of rows (1500)/number of buckets (10). The list of
numbers for the “buckets” property indicates bucket boundaries, with the first
bucket starting at 0.0 and ending at 2.0. The end of the first bucket is the
start point for the second bucket, such that the second bucket starts at 2.0
and ends at 4.0, and so on for the remainder of the buckets.
diff --git a/_docs/sql-reference/sql-commands/011-refresh-table-metadata.md
b/_docs/sql-reference/sql-commands/011-refresh-table-metadata.md
index ebfbb28..c2ddca0 100644
--- a/_docs/sql-reference/sql-commands/011-refresh-table-metadata.md
+++ b/_docs/sql-reference/sql-commands/011-refresh-table-metadata.md
@@ -1,6 +1,6 @@
---
title: "REFRESH TABLE METADATA"
-date: 2019-05-24
+date: 2019-05-31
parent: "SQL Commands"
---
Run the REFRESH TABLE METADATA command on Parquet tables and directories to
generate a metadata cache file. REFRESH TABLE METADATA collects metadata from
the footers of Parquet files and writes the metadata to a metadata file
(`.drill.parquet_file_metadata.v4`) and a summary file
(`.drill.parquet_summary_metadata.v4`). The planner uses the metadata cache
file to prune extraneous data during the query planning phase. Run the REFRESH
TABLE METADATA command if planning time is a significant [...]
@@ -97,7 +97,7 @@ These examples use a schema, `dfs.samples`, which points to
the `/tmp` directory
**Note:** You can access the sample `nation.parquet` file in the `sample-data`
directory of your Drill installation.
-Change schemas to switch to `dfs.samples`:
+Change to the `dfs.samples` schema:
use dfs.samples;
+-------+------------------------------------------+
diff --git a/_docs/sql-reference/sql-commands/021-create-schema.md
b/_docs/sql-reference/sql-commands/021-create-schema.md
index 7477a0d..260eb38 100644
--- a/_docs/sql-reference/sql-commands/021-create-schema.md
+++ b/_docs/sql-reference/sql-commands/021-create-schema.md
@@ -1,6 +1,6 @@
---
title: "CREATE OR REPLACE SCHEMA"
-date: 2019-05-02
+date: 2019-05-31
parent: "SQL Commands"
---
@@ -625,7 +625,9 @@ You can easily drop the schema for a table using the DROP
SCHEMA [IF EXISTS] FOR
##Troubleshooting
**Schema defined as incorrect data type produces DATA_READ_ERROR**
-Assume that you defined schema on the “name” column as integer, as shown:
+
+Assume that you defined schema on the “name” column as integer, as shown:
+
create or replace schema (name int) for table dfs.tmp.`text_table`;
+------+-----------------------------------------+
| ok | summary |
