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The following commit(s) were added to refs/heads/asf-site by this push: new 0ceaaaf528 Fix the CSS of Spark 3.5.0 doc's generated tables (#492) 0ceaaaf528 is described below commit 0ceaaaf528ec1d0201e1eab1288f37cce607268b Author: Gengliang Wang <gengli...@apache.org> AuthorDate: Thu Nov 30 15:06:18 2023 -0800 Fix the CSS of Spark 3.5.0 doc's generated tables (#492) After https://github.com/apache/spark/pull/40269, there is no border in the generated tables of Spark doc(for example, [sql-ref-ansi-compliance.html](https://spark.apache.org/docs/latest/sql-ref-ansi-compliance.html)) . Currently only the doc of Spark 3.5.0 is affected. This PR is to apply the changes in https://github.com/apache/spark/pull/44096 on the current Spark 3.5.0 doc by 1. change the `site/docs/3.5.0/css/custom.css` 2. Execute `sed -i '' 's/table class="table table-striped"/table/' *.html` under `site/docs/3.5.0/` directory. This should be a safe change. I have verified it on my local env. --- site/docs/3.5.0/building-spark.html | 2 +- site/docs/3.5.0/cluster-overview.html | 2 +- site/docs/3.5.0/configuration.html | 40 +++++++++++----------- site/docs/3.5.0/css/custom.css | 13 +++++++ site/docs/3.5.0/ml-classification-regression.html | 14 ++++---- site/docs/3.5.0/ml-clustering.html | 8 ++--- .../3.5.0/mllib-classification-regression.html | 2 +- site/docs/3.5.0/mllib-decision-tree.html | 2 +- site/docs/3.5.0/mllib-ensembles.html | 2 +- site/docs/3.5.0/mllib-evaluation-metrics.html | 10 +++--- site/docs/3.5.0/mllib-linear-methods.html | 4 +-- site/docs/3.5.0/mllib-pmml-model-export.html | 2 +- site/docs/3.5.0/monitoring.html | 10 +++--- site/docs/3.5.0/rdd-programming-guide.html | 8 ++--- site/docs/3.5.0/running-on-kubernetes.html | 8 ++--- site/docs/3.5.0/running-on-mesos.html | 2 +- site/docs/3.5.0/running-on-yarn.html | 8 ++--- site/docs/3.5.0/security.html | 26 +++++++------- site/docs/3.5.0/spark-standalone.html | 12 +++---- site/docs/3.5.0/sparkr.html | 6 ++-- site/docs/3.5.0/sql-data-sources-avro.html | 12 +++---- site/docs/3.5.0/sql-data-sources-csv.html | 2 +- site/docs/3.5.0/sql-data-sources-hive-tables.html | 4 +-- site/docs/3.5.0/sql-data-sources-jdbc.html | 2 +- site/docs/3.5.0/sql-data-sources-json.html | 2 +- .../sql-data-sources-load-save-functions.html | 2 +- site/docs/3.5.0/sql-data-sources-orc.html | 4 +-- site/docs/3.5.0/sql-data-sources-parquet.html | 4 +-- site/docs/3.5.0/sql-data-sources-text.html | 2 +- .../sql-distributed-sql-engine-spark-sql-cli.html | 4 +-- .../docs/3.5.0/sql-error-conditions-sqlstates.html | 26 +++++++------- site/docs/3.5.0/sql-migration-guide.html | 4 +-- site/docs/3.5.0/sql-performance-tuning.html | 16 ++++----- site/docs/3.5.0/storage-openstack-swift.html | 2 +- site/docs/3.5.0/streaming-custom-receivers.html | 2 +- site/docs/3.5.0/streaming-programming-guide.html | 10 +++--- .../structured-streaming-kafka-integration.html | 20 +++++------ .../structured-streaming-programming-guide.html | 12 +++---- site/docs/3.5.0/submitting-applications.html | 2 +- site/docs/3.5.0/web-ui.html | 2 +- 40 files changed, 164 insertions(+), 151 deletions(-) diff --git a/site/docs/3.5.0/building-spark.html b/site/docs/3.5.0/building-spark.html index 0af9dd6517..672d686bc3 100644 --- a/site/docs/3.5.0/building-spark.html +++ b/site/docs/3.5.0/building-spark.html @@ -481,7 +481,7 @@ Change the major Scala version using (e.g. 2.13):</p> <h3 id="related-environment-variables">Related environment variables</h3> -<table class="table table-striped"> +<table> <thead><tr><th>Variable Name</th><th>Default</th><th>Meaning</th></tr></thead> <tr> <td><code>SPARK_PROJECT_URL</code></td> diff --git a/site/docs/3.5.0/cluster-overview.html b/site/docs/3.5.0/cluster-overview.html index d6015a8686..552b24b729 100644 --- a/site/docs/3.5.0/cluster-overview.html +++ b/site/docs/3.5.0/cluster-overview.html @@ -216,7 +216,7 @@ The <a href="job-scheduling.html">job scheduling overview</a> describes this in <p>The following table summarizes terms you’ll see used to refer to cluster concepts:</p> -<table class="table table-striped"> +<table> <thead> <tr><th style="width: 130px;">Term</th><th>Meaning</th></tr> </thead> diff --git a/site/docs/3.5.0/configuration.html b/site/docs/3.5.0/configuration.html index d6c9255302..3ca1684ffd 100644 --- a/site/docs/3.5.0/configuration.html +++ b/site/docs/3.5.0/configuration.html @@ -309,7 +309,7 @@ of the most common options to set are:</p> <h3 id="application-properties">Application Properties</h3> -<table class="table table-striped"> +<table> <thead><tr><th>Property Name</th><th>Default</th><th>Meaning</th><th>Since Version</th></tr></thead> <tr> <td><code>spark.app.name</code></td> @@ -694,7 +694,7 @@ of the most common options to set are:</p> <h3 id="runtime-environment">Runtime Environment</h3> -<table class="table table-striped"> +<table> <thead><tr><th>Property Name</th><th>Default</th><th>Meaning</th><th>Since Version</th></tr></thead> <tr> <td><code>spark.driver.extraClassPath</code></td> @@ -1081,7 +1081,7 @@ of the most common options to set are:</p> <h3 id="shuffle-behavior">Shuffle Behavior</h3> -<table class="table table-striped"> +<table> <thead><tr><th>Property Name</th><th>Default</th><th>Meaning</th><th>Since Version</th></tr></thead> <tr> <td><code>spark.reducer.maxSizeInFlight</code></td> @@ -1456,7 +1456,7 @@ of the most common options to set are:</p> <h3 id="spark-ui">Spark UI</h3> -<table class="table table-striped"> +<table> <thead><tr><th>Property Name</th><th>Default</th><th>Meaning</th><th>Since Version</th></tr></thead> <tr> <td><code>spark.eventLog.logBlockUpdates.enabled</code></td> @@ -1848,7 +1848,7 @@ of the most common options to set are:</p> <h3 id="compression-and-serialization">Compression and Serialization</h3> -<table class="table table-striped"> +<table> <thead><tr><th>Property Name</th><th>Default</th><th>Meaning</th><th>Since Version</th></tr></thead> <tr> <td><code>spark.broadcast.compress</code></td> @@ -2046,7 +2046,7 @@ of the most common options to set are:</p> <h3 id="memory-management">Memory Management</h3> -<table class="table table-striped"> +<table> <thead><tr><th>Property Name</th><th>Default</th><th>Meaning</th><th>Since Version</th></tr></thead> <tr> <td><code>spark.memory.fraction</code></td> @@ -2171,7 +2171,7 @@ of the most common options to set are:</p> <h3 id="execution-behavior">Execution Behavior</h3> -<table class="table table-striped"> +<table> <thead><tr><th>Property Name</th><th>Default</th><th>Meaning</th><th>Since Version</th></tr></thead> <tr> <td><code>spark.broadcast.blockSize</code></td> @@ -2421,7 +2421,7 @@ of the most common options to set are:</p> <h3 id="executor-metrics">Executor Metrics</h3> -<table class="table table-striped"> +<table> <thead><tr><th>Property Name</th><th>Default</th><th>Meaning</th><th>Since Version</th></tr></thead> <tr> <td><code>spark.eventLog.logStageExecutorMetrics</code></td> @@ -2489,7 +2489,7 @@ of the most common options to set are:</p> <h3 id="networking">Networking</h3> -<table class="table table-striped"> +<table> <thead><tr><th>Property Name</th><th>Default</th><th>Meaning</th><th>Since Version</th></tr></thead> <tr> <td><code>spark.rpc.message.maxSize</code></td> @@ -2652,7 +2652,7 @@ of the most common options to set are:</p> <h3 id="scheduling">Scheduling</h3> -<table class="table table-striped"> +<table> <thead><tr><th>Property Name</th><th>Default</th><th>Meaning</th><th>Since Version</th></tr></thead> <tr> <td><code>spark.cores.max</code></td> @@ -3136,7 +3136,7 @@ of the most common options to set are:</p> <h3 id="barrier-execution-mode">Barrier Execution Mode</h3> -<table class="table table-striped"> +<table> <thead><tr><th>Property Name</th><th>Default</th><th>Meaning</th><th>Since Version</th></tr></thead> <tr> <td><code>spark.barrier.sync.timeout</code></td> @@ -3183,7 +3183,7 @@ of the most common options to set are:</p> <h3 id="dynamic-allocation">Dynamic Allocation</h3> -<table class="table table-striped"> +<table> <thead><tr><th>Property Name</th><th>Default</th><th>Meaning</th><th>Since Version</th></tr></thead> <tr> <td><code>spark.dynamicAllocation.enabled</code></td> @@ -3325,7 +3325,7 @@ finer granularity starting from driver and executor. Take RPC module as example like shuffle, just replace “rpc” with “shuffle” in the property names except <code>spark.{driver|executor}.rpc.netty.dispatcher.numThreads</code>, which is only for RPC module.</p> -<table class="table table-striped"> +<table> <thead><tr><th>Property Name</th><th>Default</th><th>Meaning</th><th>Since Version</th></tr></thead> <tr> <td><code>spark.{driver|executor}.rpc.io.serverThreads</code></td> @@ -4923,7 +4923,7 @@ Note that 1, 2, and 3 support wildcard. For example: <h3 id="spark-streaming">Spark Streaming</h3> -<table class="table table-striped"> +<table> <thead><tr><th>Property Name</th><th>Default</th><th>Meaning</th><th>Since Version</th></tr></thead> <tr> <td><code>spark.streaming.backpressure.enabled</code></td> @@ -5055,7 +5055,7 @@ Note that 1, 2, and 3 support wildcard. For example: <h3 id="sparkr">SparkR</h3> -<table class="table table-striped"> +<table> <thead><tr><th>Property Name</th><th>Default</th><th>Meaning</th><th>Since Version</th></tr></thead> <tr> <td><code>spark.r.numRBackendThreads</code></td> @@ -5111,7 +5111,7 @@ Note that 1, 2, and 3 support wildcard. For example: <h3 id="graphx">GraphX</h3> -<table class="table table-striped"> +<table> <thead><tr><th>Property Name</th><th>Default</th><th>Meaning</th><th>Since Version</th></tr></thead> <tr> <td><code>spark.graphx.pregel.checkpointInterval</code></td> @@ -5126,7 +5126,7 @@ Note that 1, 2, and 3 support wildcard. For example: <h3 id="deploy">Deploy</h3> -<table class="table table-striped"> +<table> <thead><tr><th>Property Name</th><th>Default</th><th>Meaning</th><th>Since Version</th></tr></thead> <tr> <td><code>spark.deploy.recoveryMode</code></td> @@ -5174,7 +5174,7 @@ copy <code class="language-plaintext highlighter-rouge">conf/spark-env.sh.templa <p>The following variables can be set in <code class="language-plaintext highlighter-rouge">spark-env.sh</code>:</p> -<table class="table table-striped"> +<table> <thead><tr><th style="width:21%">Environment Variable</th><th>Meaning</th></tr></thead> <tr> <td><code>JAVA_HOME</code></td> @@ -5310,7 +5310,7 @@ This is only available for the RDD API in Scala, Java, and Python. It is availa <h3 id="external-shuffle-serviceserver-side-configuration-options">External Shuffle service(server) side configuration options</h3> -<table class="table table-striped"> +<table> <thead><tr><th>Property Name</th><th>Default</th><th>Meaning</th><th>Since Version</th></tr></thead> <tr> <td><code>spark.shuffle.push.server.mergedShuffleFileManagerImpl</code></td> @@ -5344,7 +5344,7 @@ This is only available for the RDD API in Scala, Java, and Python. It is availa <h3 id="client-side-configuration-options">Client side configuration options</h3> -<table class="table table-striped"> +<table> <thead><tr><th>Property Name</th><th>Default</th><th>Meaning</th><th>Since Version</th></tr></thead> <tr> <td><code>spark.shuffle.push.enabled</code></td> diff --git a/site/docs/3.5.0/css/custom.css b/site/docs/3.5.0/css/custom.css index 4576f45d1a..e7416d9ded 100644 --- a/site/docs/3.5.0/css/custom.css +++ b/site/docs/3.5.0/css/custom.css @@ -1110,5 +1110,18 @@ img { table { width: 100%; overflow-wrap: normal; + border-collapse: collapse; /* Ensures that the borders collapse into a single border */ } +table th, table td { + border: 1px solid #cccccc; /* Adds a border to each table header and data cell */ + padding: 6px 13px; /* Optional: Adds padding inside each cell for better readability */ +} + +table tr { + background-color: white; /* Sets a default background color for all rows */ +} + +table tr:nth-child(2n) { + background-color: #F1F4F5; /* Sets a different background color for even rows */ +} diff --git a/site/docs/3.5.0/ml-classification-regression.html b/site/docs/3.5.0/ml-classification-regression.html index 6cc40fbd85..83c236fad2 100644 --- a/site/docs/3.5.0/ml-classification-regression.html +++ b/site/docs/3.5.0/ml-classification-regression.html @@ -2705,7 +2705,7 @@ others.</p> <h3 id="available-families">Available families</h3> -<table class="table table-striped"> +<table> <thead> <tr> <th>Family</th> @@ -4147,7 +4147,7 @@ All output columns are optional; to exclude an output column, set its correspond <h3 id="input-columns">Input Columns</h3> -<table class="table table-striped"> +<table> <thead> <tr> <th align="left">Param name</th> @@ -4174,7 +4174,7 @@ All output columns are optional; to exclude an output column, set its correspond <h3 id="output-columns">Output Columns</h3> -<table class="table table-striped"> +<table> <thead> <tr> <th align="left">Param name</th> @@ -4250,7 +4250,7 @@ All output columns are optional; to exclude an output column, set its correspond <h4 id="input-columns-1">Input Columns</h4> -<table class="table table-striped"> +<table> <thead> <tr> <th align="left">Param name</th> @@ -4277,7 +4277,7 @@ All output columns are optional; to exclude an output column, set its correspond <h4 id="output-columns-predictions">Output Columns (Predictions)</h4> -<table class="table table-striped"> +<table> <thead> <tr> <th align="left">Param name</th> @@ -4329,7 +4329,7 @@ All output columns are optional; to exclude an output column, set its correspond <h4 id="input-columns-2">Input Columns</h4> -<table class="table table-striped"> +<table> <thead> <tr> <th align="left">Param name</th> @@ -4358,7 +4358,7 @@ All output columns are optional; to exclude an output column, set its correspond <h4 id="output-columns-predictions-1">Output Columns (Predictions)</h4> -<table class="table table-striped"> +<table> <thead> <tr> <th align="left">Param name</th> diff --git a/site/docs/3.5.0/ml-clustering.html b/site/docs/3.5.0/ml-clustering.html index ccc0cb191b..f093bf505e 100644 --- a/site/docs/3.5.0/ml-clustering.html +++ b/site/docs/3.5.0/ml-clustering.html @@ -402,7 +402,7 @@ called <a href="http://theory.stanford.edu/~sergei/papers/vldb12-kmpar.pdf">kmea <h3 id="input-columns">Input Columns</h3> -<table class="table table-striped"> +<table> <thead> <tr> <th align="left">Param name</th> @@ -423,7 +423,7 @@ called <a href="http://theory.stanford.edu/~sergei/papers/vldb12-kmpar.pdf">kmea <h3 id="output-columns">Output Columns</h3> -<table class="table table-striped"> +<table> <thead> <tr> <th align="left">Param name</th> @@ -840,7 +840,7 @@ model.</p> <h3 id="input-columns-1">Input Columns</h3> -<table class="table table-striped"> +<table> <thead> <tr> <th align="left">Param name</th> @@ -861,7 +861,7 @@ model.</p> <h3 id="output-columns-1">Output Columns</h3> -<table class="table table-striped"> +<table> <thead> <tr> <th align="left">Param name</th> diff --git a/site/docs/3.5.0/mllib-classification-regression.html b/site/docs/3.5.0/mllib-classification-regression.html index b4eb93ff39..f052d69fba 100644 --- a/site/docs/3.5.0/mllib-classification-regression.html +++ b/site/docs/3.5.0/mllib-classification-regression.html @@ -431,7 +431,7 @@ classification</a>, and <a href="http://en.wikipedia.org/wiki/Regression_analysis">regression analysis</a>. The table below outlines the supported algorithms for each type of problem.</p> -<table class="table table-striped"> +<table> <thead> <tr><th>Problem Type</th><th>Supported Methods</th></tr> </thead> diff --git a/site/docs/3.5.0/mllib-decision-tree.html b/site/docs/3.5.0/mllib-decision-tree.html index a673501145..a92c22b494 100644 --- a/site/docs/3.5.0/mllib-decision-tree.html +++ b/site/docs/3.5.0/mllib-decision-tree.html @@ -419,7 +419,7 @@ is the information gain when a split <code class="language-plaintext highlighter implementation provides two impurity measures for classification (Gini impurity and entropy) and one impurity measure for regression (variance).</p> -<table class="table table-striped"> +<table> <thead> <tr><th>Impurity</th><th>Task</th><th>Formula</th><th>Description</th></tr> </thead> diff --git a/site/docs/3.5.0/mllib-ensembles.html b/site/docs/3.5.0/mllib-ensembles.html index a075e72cd5..4e606b517d 100644 --- a/site/docs/3.5.0/mllib-ensembles.html +++ b/site/docs/3.5.0/mllib-ensembles.html @@ -818,7 +818,7 @@ Note that each loss is applicable to one of classification or regression, not bo <p>Notation: $N$ = number of instances. $y_i$ = label of instance $i$. $x_i$ = features of instance $i$. $F(x_i)$ = model’s predicted label for instance $i$.</p> -<table class="table table-striped"> +<table> <thead> <tr><th>Loss</th><th>Task</th><th>Formula</th><th>Description</th></tr> </thead> diff --git a/site/docs/3.5.0/mllib-evaluation-metrics.html b/site/docs/3.5.0/mllib-evaluation-metrics.html index 49f9c4734e..f0ac45379c 100644 --- a/site/docs/3.5.0/mllib-evaluation-metrics.html +++ b/site/docs/3.5.0/mllib-evaluation-metrics.html @@ -441,7 +441,7 @@ plots (recall, false positive rate) points.</p> <p><strong>Available metrics</strong></p> -<table class="table table-striped"> +<table> <thead> <tr><th>Metric</th><th>Definition</th></tr> </thead> @@ -706,7 +706,7 @@ correctly normalized by the number of times that label appears in the output.</p \[\hat{\delta}(x) = \begin{cases}1 & \text{if $x = 0$}, \\ 0 & \text{otherwise}.\end{cases}\] -<table class="table table-striped"> +<table> <thead> <tr><th>Metric</th><th>Definition</th></tr> </thead> @@ -983,7 +983,7 @@ correspond to document $d_i$.</p> \[I_A(x) = \begin{cases}1 & \text{if $x \in A$}, \\ 0 & \text{otherwise}.\end{cases}\] -<table class="table table-striped"> +<table> <thead> <tr><th>Metric</th><th>Definition</th></tr> </thead> @@ -1263,7 +1263,7 @@ documents, returns a relevance score for the recommended document.</p> \[rel_D(r) = \begin{cases}1 & \text{if $r \in D$}, \\ 0 & \text{otherwise}.\end{cases}\] -<table class="table table-striped"> +<table> <thead> <tr><th>Metric</th><th>Definition</th><th>Notes</th></tr> </thead> @@ -1595,7 +1595,7 @@ variable from a number of independent variables.</p> <p><strong>Available metrics</strong></p> -<table class="table table-striped"> +<table> <thead> <tr><th>Metric</th><th>Definition</th></tr> </thead> diff --git a/site/docs/3.5.0/mllib-linear-methods.html b/site/docs/3.5.0/mllib-linear-methods.html index d133fefd8f..09542778e6 100644 --- a/site/docs/3.5.0/mllib-linear-methods.html +++ b/site/docs/3.5.0/mllib-linear-methods.html @@ -437,7 +437,7 @@ training error) and minimizing model complexity (i.e., to avoid overfitting).</p <p>The following table summarizes the loss functions and their gradients or sub-gradients for the methods <code class="language-plaintext highlighter-rouge">spark.mllib</code> supports:</p> -<table class="table table-striped"> +<table> <thead> <tr><th></th><th>loss function $L(\wv; \x, y)$</th><th>gradient or sub-gradient</th></tr> </thead> @@ -470,7 +470,7 @@ multiclass labeling.</p> encourage simple models and avoid overfitting. We support the following regularizers in <code class="language-plaintext highlighter-rouge">spark.mllib</code>:</p> -<table class="table table-striped"> +<table> <thead> <tr><th></th><th>regularizer $R(\wv)$</th><th>gradient or sub-gradient</th></tr> </thead> diff --git a/site/docs/3.5.0/mllib-pmml-model-export.html b/site/docs/3.5.0/mllib-pmml-model-export.html index b2f44ec56b..4621af6ae9 100644 --- a/site/docs/3.5.0/mllib-pmml-model-export.html +++ b/site/docs/3.5.0/mllib-pmml-model-export.html @@ -379,7 +379,7 @@ <p>The table below outlines the <code class="language-plaintext highlighter-rouge">spark.mllib</code> models that can be exported to PMML and their equivalent PMML model.</p> -<table class="table table-striped"> +<table> <thead> <tr><th>spark.mllib model</th><th>PMML model</th></tr> </thead> diff --git a/site/docs/3.5.0/monitoring.html b/site/docs/3.5.0/monitoring.html index bfc9e8e235..fd254e8d86 100644 --- a/site/docs/3.5.0/monitoring.html +++ b/site/docs/3.5.0/monitoring.html @@ -226,7 +226,7 @@ spark.eventLog.dir hdfs://namenode/shared/spark-logs <h3 id="environment-variables">Environment Variables</h3> -<table class="table table-striped"> +<table> <thead><tr><th style="width:21%">Environment Variable</th><th>Meaning</th></tr></thead> <tr> <td><code>SPARK_DAEMON_MEMORY</code></td> @@ -304,7 +304,7 @@ Use it with caution.</p> <p>Security options for the Spark History Server are covered more detail in the <a href="security.html#web-ui">Security</a> page.</p> -<table class="table table-striped"> +<table> <thead> <tr> <th>Property Name</th> @@ -635,7 +635,7 @@ only for applications in cluster mode, not applications in client mode. Applicat can be identified by their <code class="language-plaintext highlighter-rouge">[attempt-id]</code>. In the API listed below, when running in YARN cluster mode, <code class="language-plaintext highlighter-rouge">[app-id]</code> will actually be <code class="language-plaintext highlighter-rouge">[base-app-id]/[attempt-id]</code>, where <code class="language-plaintext highlighter-rouge">[base-app-id]</code> is the YARN application ID.</p> -<table class="table table-striped"> +<table> <thead><tr><th>Endpoint</th><th>Meaning</th></tr></thead> <tr> <td><code>/applications</code></td> @@ -834,7 +834,7 @@ more entries by increasing these values and restarting the history server.</p> of task execution. The metrics can be used for performance troubleshooting and workload characterization. A list of the available metrics, with a short description:</p> -<table class="table table-striped"> +<table> <thead> <tr> <th>Spark Executor Task Metric name</th> @@ -992,7 +992,7 @@ In addition, aggregated per-stage peak values of the executor memory metrics are Executor memory metrics are also exposed via the Spark metrics system based on the <a href="https://metrics.dropwizard.io/4.2.0">Dropwizard metrics library</a>. A list of the available metrics, with a short description:</p> -<table class="table table-striped"> +<table> <thead> <tr><th>Executor Level Metric name</th> <th>Short description</th> diff --git a/site/docs/3.5.0/rdd-programming-guide.html b/site/docs/3.5.0/rdd-programming-guide.html index f6c3bbf095..3df7363e05 100644 --- a/site/docs/3.5.0/rdd-programming-guide.html +++ b/site/docs/3.5.0/rdd-programming-guide.html @@ -518,7 +518,7 @@ resulting Java objects using <a href="https://github.com/irmen/pickle/">pickle</ PySpark does the reverse. It unpickles Python objects into Java objects and then converts them to Writables. The following Writables are automatically converted:</p> - <table class="table table-striped"> + <table> <thead><tr><th>Writable Type</th><th>Python Type</th></tr></thead> <tr><td>Text</td><td>str</td></tr> <tr><td>IntWritable</td><td>int</td></tr> @@ -1079,7 +1079,7 @@ and pair RDD functions doc <a href="api/java/index.html?org/apache/spark/api/java/JavaPairRDD.html">Java</a>) for details.</p> -<table class="table table-striped"> +<table> <thead><tr><th style="width:25%">Transformation</th><th>Meaning</th></tr></thead> <tr> <td> <b>map</b>(<i>func</i>) </td> @@ -1194,7 +1194,7 @@ RDD API doc <a href="api/java/index.html?org/apache/spark/api/java/JavaPairRDD.html">Java</a>) for details.</p> -<table class="table table-striped"> +<table> <thead><tr><th>Action</th><th>Meaning</th></tr></thead> <tr> <td> <b>reduce</b>(<i>func</i>) </td> @@ -1340,7 +1340,7 @@ to <code class="language-plaintext highlighter-rouge">persist()</code>. The <cod which is <code class="language-plaintext highlighter-rouge">StorageLevel.MEMORY_ONLY</code> (store deserialized objects in memory). The full set of storage levels is:</p> -<table class="table table-striped"> +<table> <thead><tr><th style="width:23%">Storage Level</th><th>Meaning</th></tr></thead> <tr> <td> MEMORY_ONLY </td> diff --git a/site/docs/3.5.0/running-on-kubernetes.html b/site/docs/3.5.0/running-on-kubernetes.html index fe79c79d9d..045a7db2f3 100644 --- a/site/docs/3.5.0/running-on-kubernetes.html +++ b/site/docs/3.5.0/running-on-kubernetes.html @@ -757,7 +757,7 @@ using <code class="language-plaintext highlighter-rouge">--conf</code> as means <h4 id="spark-properties">Spark Properties</h4> -<table class="table table-striped"> +<table> <thead><tr><th>Property Name</th><th>Default</th><th>Meaning</th><th>Since Version</th></tr></thead> <tr> <td><code>spark.kubernetes.context</code></td> @@ -1823,7 +1823,7 @@ using <code class="language-plaintext highlighter-rouge">--conf</code> as means <h3 id="pod-metadata">Pod Metadata</h3> -<table class="table table-striped"> +<table> <thead><tr><th>Pod metadata key</th><th>Modified value</th><th>Description</th></tr></thead> <tr> <td>name</td> @@ -1859,7 +1859,7 @@ using <code class="language-plaintext highlighter-rouge">--conf</code> as means <h3 id="pod-spec">Pod Spec</h3> -<table class="table table-striped"> +<table> <thead><tr><th>Pod spec key</th><th>Modified value</th><th>Description</th></tr></thead> <tr> <td>imagePullSecrets</td> @@ -1912,7 +1912,7 @@ using <code class="language-plaintext highlighter-rouge">--conf</code> as means <p>The following affect the driver and executor containers. All other containers in the pod spec will be unaffected.</p> -<table class="table table-striped"> +<table> <thead><tr><th>Container spec key</th><th>Modified value</th><th>Description</th></tr></thead> <tr> <td>env</td> diff --git a/site/docs/3.5.0/running-on-mesos.html b/site/docs/3.5.0/running-on-mesos.html index 8a3f5bb10f..08f8128af3 100644 --- a/site/docs/3.5.0/running-on-mesos.html +++ b/site/docs/3.5.0/running-on-mesos.html @@ -536,7 +536,7 @@ termination. To launch it, run <code class="language-plaintext highlighter-rouge <h4 id="spark-properties">Spark Properties</h4> -<table class="table table-striped"> +<table> <thead><tr><th>Property Name</th><th>Default</th><th>Meaning</th><th>Since Version</th></tr></thead> <tr> <td><code>spark.mesos.coarse</code></td> diff --git a/site/docs/3.5.0/running-on-yarn.html b/site/docs/3.5.0/running-on-yarn.html index 6b6337da4c..0ee92f2b8f 100644 --- a/site/docs/3.5.0/running-on-yarn.html +++ b/site/docs/3.5.0/running-on-yarn.html @@ -295,7 +295,7 @@ to the same log file).</p> <h4 id="spark-properties">Spark Properties</h4> -<table class="table table-striped"> +<table> <thead><tr><th>Property Name</th><th>Default</th><th>Meaning</th><th>Since Version</th></tr></thead> <tr> <td><code>spark.yarn.am.memory</code></td> @@ -848,7 +848,7 @@ to the same log file).</p> <h4 id="available-patterns-for-shs-custom-executor-log-url">Available patterns for SHS custom executor log URL</h4> -<table class="table table-striped"> +<table> <thead><tr><th>Pattern</th><th>Meaning</th></tr></thead> <tr> <td>{{HTTP_SCHEME}}</td> @@ -933,7 +933,7 @@ staging directory of the Spark application.</p> <h2 id="yarn-specific-kerberos-configuration">YARN-specific Kerberos Configuration</h2> -<table class="table table-striped"> +<table> <thead><tr><th>Property Name</th><th>Default</th><th>Meaning</th><th>Since Version</th></tr></thead> <tr> <td><code>spark.kerberos.keytab</code></td> @@ -1030,7 +1030,7 @@ to avoid garbage collection issues during shuffle.</li> <p>The following extra configuration options are available when the shuffle service is running on YARN:</p> -<table class="table table-striped"> +<table> <thead><tr><th>Property Name</th><th>Default</th><th>Meaning</th></tr></thead> <tr> <td><code>spark.yarn.shuffle.stopOnFailure</code></td> diff --git a/site/docs/3.5.0/security.html b/site/docs/3.5.0/security.html index 97f7bf7581..39131daa90 100644 --- a/site/docs/3.5.0/security.html +++ b/site/docs/3.5.0/security.html @@ -221,7 +221,7 @@ distributing the shared secret. Each application will use a unique shared secret the case of YARN, this feature relies on YARN RPC encryption being enabled for the distribution of secrets to be secure.</p> -<table class="table table-striped"> +<table> <thead><tr><th>Property Name</th><th>Default</th><th>Meaning</th><th>Since Version</th></tr></thead> <tr> <td><code>spark.yarn.shuffle.server.recovery.disabled</code></td> @@ -243,7 +243,7 @@ that any user that can list pods in the namespace where the Spark application is also see their authentication secret. Access control rules should be properly set up by the Kubernetes admin to ensure that Spark authentication is secure.</p> -<table class="table table-striped"> +<table> <thead><tr><th>Property Name</th><th>Default</th><th>Meaning</th><th>Since Version</th></tr></thead> <tr> <td><code>spark.authenticate</code></td> @@ -264,7 +264,7 @@ Kubernetes admin to ensure that Spark authentication is secure.</p> <p>Alternatively, one can mount authentication secrets using files and Kubernetes secrets that the user mounts into their pods.</p> -<table class="table table-striped"> +<table> <thead><tr><th>Property Name</th><th>Default</th><th>Meaning</th><th>Since Version</th></tr></thead> <tr> <td><code>spark.authenticate.secret.file</code></td> @@ -320,7 +320,7 @@ is still required when talking to shuffle services from Spark versions older tha <p>The following table describes the different options available for configuring this feature.</p> -<table class="table table-striped"> +<table> <thead><tr><th>Property Name</th><th>Default</th><th>Meaning</th><th>Since Version</th></tr></thead> <tr> <td><code>spark.network.crypto.enabled</code></td> @@ -379,7 +379,7 @@ encrypting output data generated by applications with APIs such as <code class=" <p>The following settings cover enabling encryption for data written to disk:</p> -<table class="table table-striped"> +<table> <thead><tr><th>Property Name</th><th>Default</th><th>Meaning</th><th>Since Version</th></tr></thead> <tr> <td><code>spark.io.encryption.enabled</code></td> @@ -446,7 +446,7 @@ below.</p> <p>The following options control the authentication of Web UIs:</p> -<table class="table table-striped"> +<table> <thead><tr><th>Property Name</th><th>Default</th><th>Meaning</th><th>Since Version</th></tr></thead> <tr> <td><code>spark.ui.allowFramingFrom</code></td> @@ -550,7 +550,7 @@ servlet filters.</p> <p>To enable authorization in the SHS, a few extra options are used:</p> -<table class="table table-striped"> +<table> <thead><tr><th>Property Name</th><th>Default</th><th>Meaning</th><th>Since Version</th></tr></thead> <tr> <td><code>spark.history.ui.acls.enable</code></td> @@ -599,7 +599,7 @@ protocol-specific settings. This way the user can easily provide the common sett protocols without disabling the ability to configure each one individually. The following table describes the SSL configuration namespaces:</p> -<table class="table table-striped"> +<table> <thead> <tr> <th>Config Namespace</th> @@ -630,7 +630,7 @@ describes the SSL configuration namespaces:</p> <p>The full breakdown of available SSL options can be found below. The <code class="language-plaintext highlighter-rouge">${ns}</code> placeholder should be replaced with one of the above namespaces.</p> -<table class="table table-striped"> +<table> <thead><tr><th>Property Name</th><th>Default</th><th>Meaning</th></tr></thead> <tr> <td><code>${ns}.enabled</code></td> @@ -800,7 +800,7 @@ appropriate files or environment variables.</p> (XSS), Cross-Frame Scripting (XFS), MIME-Sniffing, and also to enforce HTTP Strict Transport Security.</p> -<table class="table table-striped"> +<table> <thead><tr><th>Property Name</th><th>Default</th><th>Meaning</th><th>Since Version</th></tr></thead> <tr> <td><code>spark.ui.xXssProtection</code></td> @@ -855,7 +855,7 @@ configure those ports.</p> <h2 id="standalone-mode-only">Standalone mode only</h2> -<table class="table table-striped"> +<table> <thead> <tr> <th>From</th><th>To</th><th>Default Port</th><th>Purpose</th><th>Configuration @@ -906,7 +906,7 @@ configure those ports.</p> <h2 id="all-cluster-managers">All cluster managers</h2> -<table class="table table-striped"> +<table> <thead> <tr> <th>From</th><th>To</th><th>Default Port</th><th>Purpose</th><th>Configuration @@ -981,7 +981,7 @@ deployment-specific page for more information.</p> <p>The following options provides finer-grained control for this feature:</p> -<table class="table table-striped"> +<table> <thead><tr><th>Property Name</th><th>Default</th><th>Meaning</th><th>Since Version</th></tr></thead> <tr> <td><code>spark.security.credentials.${service}.enabled</code></td> diff --git a/site/docs/3.5.0/spark-standalone.html b/site/docs/3.5.0/spark-standalone.html index aafe485852..7c0a5ee94f 100644 --- a/site/docs/3.5.0/spark-standalone.html +++ b/site/docs/3.5.0/spark-standalone.html @@ -198,7 +198,7 @@ You should see the new node listed there, along with its number of CPUs and memo <p>Finally, the following configuration options can be passed to the master and worker:</p> -<table class="table table-striped"> +<table> <thead><tr><th style="width:21%">Argument</th><th>Meaning</th></tr></thead> <tr> <td><code>-h HOST</code>, <code>--host HOST</code></td> @@ -261,7 +261,7 @@ If you do not have a password-less setup, you can set the environment variable S <p>You can optionally configure the cluster further by setting environment variables in <code class="language-plaintext highlighter-rouge">conf/spark-env.sh</code>. Create this file by starting with the <code class="language-plaintext highlighter-rouge">conf/spark-env.sh.template</code>, and <em>copy it to all your worker machines</em> for the settings to take effect. The following settings are available:</p> -<table class="table table-striped"> +<table> <thead><tr><th style="width:21%">Environment Variable</th><th>Meaning</th></tr></thead> <tr> <td><code>SPARK_MASTER_HOST</code></td> @@ -333,7 +333,7 @@ If you do not have a password-less setup, you can set the environment variable S <p>SPARK_MASTER_OPTS supports the following system properties:</p> -<table class="table table-striped"> +<table> <thead><tr><th>Property Name</th><th>Default</th><th>Meaning</th><th>Since Version</th></tr></thead> <tr> <td><code>spark.deploy.retainedApplications</code></td> @@ -432,7 +432,7 @@ If you do not have a password-less setup, you can set the environment variable S <p>SPARK_WORKER_OPTS supports the following system properties:</p> -<table class="table table-striped"> +<table> <thead><tr><th>Property Name</th><th>Default</th><th>Meaning</th><th>Since Version</th></tr></thead> <tr> <td><code>spark.worker.cleanup.enabled</code></td> @@ -538,7 +538,7 @@ constructor</a>.</p> <p>Spark applications supports the following configuration properties specific to standalone mode:</p> -<table class="table table-striped"> +<table> <thead><tr><th style="width:21%">Property Name</th><th>Default Value</th><th>Meaning</th><th>Since Version</th></tr></thead> <tr> <td><code>spark.standalone.submit.waitAppCompletion</code></td> @@ -683,7 +683,7 @@ For more information about these configurations please refer to the <a href="con <p>In order to enable this recovery mode, you can set SPARK_DAEMON_JAVA_OPTS in spark-env using this configuration:</p> -<table class="table table-striped"> +<table> <thead><tr><th style="width:21%">System property</th><th>Meaning</th><th>Since Version</th></tr></thead> <tr> <td><code>spark.deploy.recoveryMode</code></td> diff --git a/site/docs/3.5.0/sparkr.html b/site/docs/3.5.0/sparkr.html index 99a43b78ac..488c0e27d5 100644 --- a/site/docs/3.5.0/sparkr.html +++ b/site/docs/3.5.0/sparkr.html @@ -258,7 +258,7 @@ them, pass them as you would other configuration properties in the <code class=" <p>The following Spark driver properties can be set in <code class="language-plaintext highlighter-rouge">sparkConfig</code> with <code class="language-plaintext highlighter-rouge">sparkR.session</code> from RStudio:</p> - <table class="table table-striped"> + <table> <thead><tr><th>Property Name</th><th>Property group</th><th><code>spark-submit</code> equivalent</th></tr></thead> <tr> <td><code>spark.master</code></td> @@ -782,7 +782,7 @@ SparkR supports a subset of the available R formula operators for model fitting, <div><small>Find full example code at "examples/src/main/r/ml/ml.R" in the Spark repo.</small></div> <h1 id="data-type-mapping-between-r-and-spark">Data type mapping between R and Spark</h1> -<table class="table table-striped"> +<table> <thead><tr><th>R</th><th>Spark</th></tr></thead> <tr> <td>byte</td> @@ -921,7 +921,7 @@ function is masking another function.</p> <p>The following functions are masked by the SparkR package:</p> -<table class="table table-striped"> +<table> <thead><tr><th>Masked function</th><th>How to Access</th></tr></thead> <tr> <td><code>cov</code> in <code>package:stats</code></td> diff --git a/site/docs/3.5.0/sql-data-sources-avro.html b/site/docs/3.5.0/sql-data-sources-avro.html index 8ce20afc5a..fe4a011f4a 100644 --- a/site/docs/3.5.0/sql-data-sources-avro.html +++ b/site/docs/3.5.0/sql-data-sources-avro.html @@ -585,7 +585,7 @@ Kafka key-value record will be augmented with some metadata, such as the ingesti <li>the <code class="language-plaintext highlighter-rouge">options</code> parameter in function <code class="language-plaintext highlighter-rouge">from_avro</code>.</li> </ul> -<table class="table table-striped"> +<table> <thead><tr><th><b>Property Name</b></th><th><b>Default</b></th><th><b>Meaning</b></th><th><b>Scope</b></th><th><b>Since Version</b></th></tr></thead> <tr> <td><code>avroSchema</code></td> @@ -683,7 +683,7 @@ Kafka key-value record will be augmented with some metadata, such as the ingesti <h2 id="configuration">Configuration</h2> <p>Configuration of Avro can be done using the <code class="language-plaintext highlighter-rouge">setConf</code> method on SparkSession or by running <code class="language-plaintext highlighter-rouge">SET key=value</code> commands using SQL.</p> -<table class="table table-striped"> +<table> <thead><tr><th><b>Property Name</b></th><th><b>Default</b></th><th><b>Meaning</b></th><th><b>Since Version</b></th></tr></thead> <tr> <td>spark.sql.legacy.replaceDatabricksSparkAvro.enabled</td> @@ -770,7 +770,7 @@ Submission Guide for more details.</p> <h2 id="supported-types-for-avro---spark-sql-conversion">Supported types for Avro -> Spark SQL conversion</h2> <p>Currently Spark supports reading all <a href="https://avro.apache.org/docs/1.11.2/specification/#primitive-types">primitive types</a> and <a href="https://avro.apache.org/docs/1.11.2/specification/#complex-types">complex types</a> under records of Avro.</p> -<table class="table table-striped"> +<table> <thead><tr><th><b>Avro type</b></th><th><b>Spark SQL type</b></th></tr></thead> <tr> <td>boolean</td> @@ -837,7 +837,7 @@ All other union types are considered complex. They will be mapped to StructType <p>It also supports reading the following Avro <a href="https://avro.apache.org/docs/1.11.2/specification/#logical-types">logical types</a>:</p> -<table class="table table-striped"> +<table> <thead><tr><th><b>Avro logical type</b></th><th><b>Avro type</b></th><th><b>Spark SQL type</b></th></tr></thead> <tr> <td>date</td> @@ -870,7 +870,7 @@ All other union types are considered complex. They will be mapped to StructType <h2 id="supported-types-for-spark-sql---avro-conversion">Supported types for Spark SQL -> Avro conversion</h2> <p>Spark supports writing of all Spark SQL types into Avro. For most types, the mapping from Spark types to Avro types is straightforward (e.g. IntegerType gets converted to int); however, there are a few special cases which are listed below:</p> -<table class="table table-striped"> +<table> <thead><tr><th><b>Spark SQL type</b></th><th><b>Avro type</b></th><th><b>Avro logical type</b></th></tr></thead> <tr> <td>ByteType</td> @@ -906,7 +906,7 @@ All other union types are considered complex. They will be mapped to StructType <p>You can also specify the whole output Avro schema with the option <code class="language-plaintext highlighter-rouge">avroSchema</code>, so that Spark SQL types can be converted into other Avro types. The following conversions are not applied by default and require user specified Avro schema:</p> -<table class="table table-striped"> +<table> <thead><tr><th><b>Spark SQL type</b></th><th><b>Avro type</b></th><th><b>Avro logical type</b></th></tr></thead> <tr> <td>BinaryType</td> diff --git a/site/docs/3.5.0/sql-data-sources-csv.html b/site/docs/3.5.0/sql-data-sources-csv.html index f75e1d1651..71fe964d48 100644 --- a/site/docs/3.5.0/sql-data-sources-csv.html +++ b/site/docs/3.5.0/sql-data-sources-csv.html @@ -582,7 +582,7 @@ <li><code class="language-plaintext highlighter-rouge">OPTIONS</code> clause at <a href="sql-ref-syntax-ddl-create-table-datasource.html">CREATE TABLE USING DATA_SOURCE</a></li> </ul> -<table class="table table-striped"> +<table> <thead><tr><th><b>Property Name</b></th><th><b>Default</b></th><th><b>Meaning</b></th><th><b>Scope</b></th></tr></thead> <tr> <td><code>sep</code></td> diff --git a/site/docs/3.5.0/sql-data-sources-hive-tables.html b/site/docs/3.5.0/sql-data-sources-hive-tables.html index f92935182f..51729dc5b7 100644 --- a/site/docs/3.5.0/sql-data-sources-hive-tables.html +++ b/site/docs/3.5.0/sql-data-sources-hive-tables.html @@ -711,7 +711,7 @@ format(“serde”, “input format”, “output formatR By default, we will read the table files as plain text. Note that, Hive storage handler is not supported yet when creating table, you can create a table using storage handler at Hive side, and use Spark SQL to read it.</p> -<table class="table table-striped"> +<table> <thead><tr><th>Property Name</th><th>Meaning</th></tr></thead> <tr> <td><code>fileFormat</code></td> @@ -759,7 +759,7 @@ will compile against built-in Hive and use those classes for internal execution <p>The following options can be used to configure the version of Hive that is used to retrieve metadata:</p> -<table class="table table-striped"> +<table> <thead><tr><th>Property Name</th><th>Default</th><th>Meaning</th><th>Since Version</th></tr></thead> <tr> <td><code>spark.sql.hive.metastore.version</code></td> diff --git a/site/docs/3.5.0/sql-data-sources-jdbc.html b/site/docs/3.5.0/sql-data-sources-jdbc.html index 70bf62a979..4cbd6bad6c 100644 --- a/site/docs/3.5.0/sql-data-sources-jdbc.html +++ b/site/docs/3.5.0/sql-data-sources-jdbc.html @@ -404,7 +404,7 @@ following command:</p> <code>user</code> and <code>password</code> are normally provided as connection properties for logging into the data sources.</p> -<table class="table table-striped"> +<table> <thead><tr><th><b>Property Name</b></th><th><b>Default</b></th><th><b>Meaning</b></th><th><b>Scope</b></th></tr></thead> <tr> <td><code>url</code></td> diff --git a/site/docs/3.5.0/sql-data-sources-json.html b/site/docs/3.5.0/sql-data-sources-json.html index 265a764e30..be3c033b56 100644 --- a/site/docs/3.5.0/sql-data-sources-json.html +++ b/site/docs/3.5.0/sql-data-sources-json.html @@ -594,7 +594,7 @@ line must contain a separate, self-contained valid JSON object. For more informa <li><code class="language-plaintext highlighter-rouge">OPTIONS</code> clause at <a href="sql-ref-syntax-ddl-create-table-datasource.html">CREATE TABLE USING DATA_SOURCE</a></li> </ul> -<table class="table table-striped"> +<table> <thead><tr><th><b>Property Name</b></th><th><b>Default</b></th><th><b>Meaning</b></th><th><b>Scope</b></th></tr></thead> <tr> <!-- TODO(SPARK-35433): Add timeZone to Data Source Option for CSV, too. --> diff --git a/site/docs/3.5.0/sql-data-sources-load-save-functions.html b/site/docs/3.5.0/sql-data-sources-load-save-functions.html index c9b568f81c..5ee1ddb7de 100644 --- a/site/docs/3.5.0/sql-data-sources-load-save-functions.html +++ b/site/docs/3.5.0/sql-data-sources-load-save-functions.html @@ -646,7 +646,7 @@ present. It is important to realize that these save modes do not utilize any loc atomic. Additionally, when performing an <code class="language-plaintext highlighter-rouge">Overwrite</code>, the data will be deleted before writing out the new data.</p> -<table class="table table-striped"> +<table> <thead><tr><th>Scala/Java</th><th>Any Language</th><th>Meaning</th></tr></thead> <tr> <td><code>SaveMode.ErrorIfExists</code> (default)</td> diff --git a/site/docs/3.5.0/sql-data-sources-orc.html b/site/docs/3.5.0/sql-data-sources-orc.html index 8f605a0927..a5a548a169 100644 --- a/site/docs/3.5.0/sql-data-sources-orc.html +++ b/site/docs/3.5.0/sql-data-sources-orc.html @@ -489,7 +489,7 @@ Please visit <a href="https://hadoop.apache.org/docs/current/hadoop-kms/index.ht <h3 id="configuration">Configuration</h3> -<table class="table table-striped"> +<table> <thead><tr><th><b>Property Name</b></th><th><b>Default</b></th><th><b>Meaning</b></th><th><b>Since Version</b></th></tr></thead> <tr> <td><code>spark.sql.orc.impl</code></td> @@ -595,7 +595,7 @@ Please visit <a href="https://hadoop.apache.org/docs/current/hadoop-kms/index.ht <li><code class="language-plaintext highlighter-rouge">OPTIONS</code> clause at <a href="sql-ref-syntax-ddl-create-table-datasource.html">CREATE TABLE USING DATA_SOURCE</a></li> </ul> -<table class="table table-striped"> +<table> <thead><tr><th><b>Property Name</b></th><th><b>Default</b></th><th><b>Meaning</b></th><th><b>Scope</b></th></tr></thead> <tr> <td><code>mergeSchema</code></td> diff --git a/site/docs/3.5.0/sql-data-sources-parquet.html b/site/docs/3.5.0/sql-data-sources-parquet.html index f612d32bfe..2b86e4ce46 100644 --- a/site/docs/3.5.0/sql-data-sources-parquet.html +++ b/site/docs/3.5.0/sql-data-sources-parquet.html @@ -954,7 +954,7 @@ metadata.</p> <li><code class="language-plaintext highlighter-rouge">OPTIONS</code> clause at <a href="sql-ref-syntax-ddl-create-table-datasource.html">CREATE TABLE USING DATA_SOURCE</a></li> </ul> -<table class="table table-striped"> +<table> <thead><tr><th><b>Property Name</b></th><th><b>Default</b></th><th><b>Meaning</b></th><th><b>Scope</b></th></tr></thead> <tr> <td><code>datetimeRebaseMode</code></td> @@ -1002,7 +1002,7 @@ metadata.</p> <p>Configuration of Parquet can be done using the <code class="language-plaintext highlighter-rouge">setConf</code> method on <code class="language-plaintext highlighter-rouge">SparkSession</code> or by running <code class="language-plaintext highlighter-rouge">SET key=value</code> commands using SQL.</p> -<table class="table table-striped"> +<table> <thead><tr><th>Property Name</th><th>Default</th><th>Meaning</th><th>Since Version</th></tr></thead> <tr> <td><code>spark.sql.parquet.binaryAsString</code></td> diff --git a/site/docs/3.5.0/sql-data-sources-text.html b/site/docs/3.5.0/sql-data-sources-text.html index ef3f2984aa..4435b391f7 100644 --- a/site/docs/3.5.0/sql-data-sources-text.html +++ b/site/docs/3.5.0/sql-data-sources-text.html @@ -530,7 +530,7 @@ <li><code class="language-plaintext highlighter-rouge">OPTIONS</code> clause at <a href="sql-ref-syntax-ddl-create-table-datasource.html">CREATE TABLE USING DATA_SOURCE</a></li> </ul> -<table class="table table-striped"> +<table> <thead><tr><th><b>Property Name</b></th><th><b>Default</b></th><th><b>Meaning</b></th><th><b>Scope</b></th></tr></thead> <tr> <td><code>wholetext</code></td> diff --git a/site/docs/3.5.0/sql-distributed-sql-engine-spark-sql-cli.html b/site/docs/3.5.0/sql-distributed-sql-engine-spark-sql-cli.html index b1473e8ce6..ea1fd70505 100644 --- a/site/docs/3.5.0/sql-distributed-sql-engine-spark-sql-cli.html +++ b/site/docs/3.5.0/sql-distributed-sql-engine-spark-sql-cli.html @@ -308,7 +308,7 @@ For example: <code class="language-plaintext highlighter-rouge">/path/to/spark-s <h2 id="supported-comment-types">Supported comment types</h2> -<table class="table table-striped"> +<table> <thead><tr><th>Comment</th><th>Example</th></tr></thead> <tr> <td>simple comment</td> @@ -362,7 +362,7 @@ Use <code class="language-plaintext highlighter-rouge">;</code> (semicolon) to t </li> </ol> -<table class="table table-striped"> +<table> <thead><tr><th>Command</th><th>Description</th></tr></thead> <tr> <td><code>quit</code> or <code>exit</code></td> diff --git a/site/docs/3.5.0/sql-error-conditions-sqlstates.html b/site/docs/3.5.0/sql-error-conditions-sqlstates.html index fbcc1fe141..38115eb954 100644 --- a/site/docs/3.5.0/sql-error-conditions-sqlstates.html +++ b/site/docs/3.5.0/sql-error-conditions-sqlstates.html @@ -462,7 +462,7 @@ Each character must be a digit <code class="language-plaintext highlighter-rouge <h2 id="class-0a-feature-not-supported">Class <code class="language-plaintext highlighter-rouge">0A</code>: feature not supported</h2> -<table class="table table-striped"> +<table> <thead><tr><th>SQLSTATE</th><th>Description and issuing error classes</th></tr></thead> <tr> <td>0A000</td> @@ -477,7 +477,7 @@ Each character must be a digit <code class="language-plaintext highlighter-rouge </table> <h2 id="class-21-cardinality-violation">Class <code class="language-plaintext highlighter-rouge">21</code>: cardinality violation</h2> -<table class="table table-striped"> +<table> <thead><tr><th>SQLSTATE</th><th>Description and issuing error classes</th></tr></thead> <tr> <td>21000</td> @@ -492,7 +492,7 @@ Each character must be a digit <code class="language-plaintext highlighter-rouge </table> <h2 id="class-22-data-exception">Class <code class="language-plaintext highlighter-rouge">22</code>: data exception</h2> -<table class="table table-striped"> +<table> <thead><tr><th>SQLSTATE</th><th>Description and issuing error classes</th></tr></thead> <tr> <td>22003</td> @@ -597,7 +597,7 @@ Each character must be a digit <code class="language-plaintext highlighter-rouge </table> <h2 id="class-23-integrity-constraint-violation">Class <code class="language-plaintext highlighter-rouge">23</code>: integrity constraint violation</h2> -<table class="table table-striped"> +<table> <thead><tr><th>SQLSTATE</th><th>Description and issuing error classes</th></tr></thead> <tr> <td>23505</td> @@ -612,7 +612,7 @@ Each character must be a digit <code class="language-plaintext highlighter-rouge </table> <h2 id="class-2b-dependent-privilege-descriptors-still-exist">Class <code class="language-plaintext highlighter-rouge">2B</code>: dependent privilege descriptors still exist</h2> -<table class="table table-striped"> +<table> <thead><tr><th>SQLSTATE</th><th>Description and issuing error classes</th></tr></thead> <tr> <td>2BP01</td> @@ -627,7 +627,7 @@ Each character must be a digit <code class="language-plaintext highlighter-rouge </table> <h2 id="class-38-external-routine-exception">Class <code class="language-plaintext highlighter-rouge">38</code>: external routine exception</h2> -<table class="table table-striped"> +<table> <thead><tr><th>SQLSTATE</th><th>Description and issuing error classes</th></tr></thead> <tr> <td>38000</td> @@ -642,7 +642,7 @@ Each character must be a digit <code class="language-plaintext highlighter-rouge </table> <h2 id="class-39-external-routine-invocation-exception">Class <code class="language-plaintext highlighter-rouge">39</code>: external routine invocation exception</h2> -<table class="table table-striped"> +<table> <thead><tr><th>SQLSTATE</th><th>Description and issuing error classes</th></tr></thead> <tr> <td>39000</td> @@ -657,7 +657,7 @@ Each character must be a digit <code class="language-plaintext highlighter-rouge </table> <h2 id="class-42-syntax-error-or-access-rule-violation">Class <code class="language-plaintext highlighter-rouge">42</code>: syntax error or access rule violation</h2> -<table class="table table-striped"> +<table> <thead><tr><th>SQLSTATE</th><th>Description and issuing error classes</th></tr></thead> <tr> <td>42000</td> @@ -1077,7 +1077,7 @@ Each character must be a digit <code class="language-plaintext highlighter-rouge </table> <h2 id="class-46-java-ddl-1">Class <code class="language-plaintext highlighter-rouge">46</code>: java ddl 1</h2> -<table class="table table-striped"> +<table> <thead><tr><th>SQLSTATE</th><th>Description and issuing error classes</th></tr></thead> <tr> <td>46110</td> @@ -1101,7 +1101,7 @@ Each character must be a digit <code class="language-plaintext highlighter-rouge </table> <h2 id="class-53-insufficient-resources">Class <code class="language-plaintext highlighter-rouge">53</code>: insufficient resources</h2> -<table class="table table-striped"> +<table> <thead><tr><th>SQLSTATE</th><th>Description and issuing error classes</th></tr></thead> <tr> <td>53200</td> @@ -1116,7 +1116,7 @@ Each character must be a digit <code class="language-plaintext highlighter-rouge </table> <h2 id="class-54-program-limit-exceeded">Class <code class="language-plaintext highlighter-rouge">54</code>: program limit exceeded</h2> -<table class="table table-striped"> +<table> <thead><tr><th>SQLSTATE</th><th>Description and issuing error classes</th></tr></thead> <tr> <td>54000</td> @@ -1131,7 +1131,7 @@ Each character must be a digit <code class="language-plaintext highlighter-rouge </table> <h2 id="class-hy-cli-specific-condition">Class <code class="language-plaintext highlighter-rouge">HY</code>: CLI-specific condition</h2> -<table class="table table-striped"> +<table> <thead><tr><th>SQLSTATE</th><th>Description and issuing error classes</th></tr></thead> <tr> <td>HY008</td> @@ -1146,7 +1146,7 @@ Each character must be a digit <code class="language-plaintext highlighter-rouge </table> <h2 id="class-xx-internal-error">Class <code class="language-plaintext highlighter-rouge">XX</code>: internal error</h2> -<table class="table table-striped"> +<table> <thead><tr><th>SQLSTATE</th><th>Description and issuing error classes</th></tr></thead> <tr> <td>XX000</td> diff --git a/site/docs/3.5.0/sql-migration-guide.html b/site/docs/3.5.0/sql-migration-guide.html index 22b49d677a..3b174cc37c 100644 --- a/site/docs/3.5.0/sql-migration-guide.html +++ b/site/docs/3.5.0/sql-migration-guide.html @@ -1026,7 +1026,7 @@ the extremely short interval that results will likely cause applications to fail <ul> <li>In Spark version 2.3 and earlier, the second parameter to array_contains function is implicitly promoted to the element type of first array type parameter. This type promotion can be lossy and may cause <code class="language-plaintext highlighter-rouge">array_contains</code> function to return wrong result. This problem has been addressed in 2.4 by employing a safer type promotion mechanism. This can cause some change in behavior and are illustrated in the table below. - <table class="table table-striped"> + <table> <thead> <tr> <th> @@ -1167,7 +1167,7 @@ the extremely short interval that results will likely cause applications to fail </li> <li> <p>Partition column inference previously found incorrect common type for different inferred types, for example, previously it ended up with double type as the common type for double type and date type. Now it finds the correct common type for such conflicts. The conflict resolution follows the table below:</p> - <table class="table table-striped"> + <table> <thead> <tr> <th> diff --git a/site/docs/3.5.0/sql-performance-tuning.html b/site/docs/3.5.0/sql-performance-tuning.html index 5db8609654..e38b9d8473 100644 --- a/site/docs/3.5.0/sql-performance-tuning.html +++ b/site/docs/3.5.0/sql-performance-tuning.html @@ -316,7 +316,7 @@ memory usage and GC pressure. You can call <code class="language-plaintext highl <p>Configuration of in-memory caching can be done using the <code class="language-plaintext highlighter-rouge">setConf</code> method on <code class="language-plaintext highlighter-rouge">SparkSession</code> or by running <code class="language-plaintext highlighter-rouge">SET key=value</code> commands using SQL.</p> -<table class="table table-striped"> +<table> <thead><tr><th>Property Name</th><th>Default</th><th>Meaning</th><th>Since Version</th></tr></thead> <tr> <td><code>spark.sql.inMemoryColumnarStorage.compressed</code></td> @@ -344,7 +344,7 @@ memory usage and GC pressure. You can call <code class="language-plaintext highl <p>The following options can also be used to tune the performance of query execution. It is possible that these options will be deprecated in future release as more optimizations are performed automatically.</p> -<table class="table table-striped"> +<table> <thead><tr><th>Property Name</th><th>Default</th><th>Meaning</th><th>Since Version</th></tr></thead> <tr> <td><code>spark.sql.files.maxPartitionBytes</code></td> @@ -524,7 +524,7 @@ hint has an initial partition number, columns, or both/neither of them as parame <h3 id="coalescing-post-shuffle-partitions">Coalescing Post Shuffle Partitions</h3> <p>This feature coalesces the post shuffle partitions based on the map output statistics when both <code class="language-plaintext highlighter-rouge">spark.sql.adaptive.enabled</code> and <code class="language-plaintext highlighter-rouge">spark.sql.adaptive.coalescePartitions.enabled</code> configurations are true. This feature simplifies the tuning of shuffle partition number when running queries. You do not need to set a proper shuffle partition number to fit your dataset. Spark can pi [...] -<table class="table table-striped"> +<table> <thead><tr><th>Property Name</th><th>Default</th><th>Meaning</th><th>Since Version</th></tr></thead> <tr> <td><code>spark.sql.adaptive.coalescePartitions.enabled</code></td> @@ -569,7 +569,7 @@ hint has an initial partition number, columns, or both/neither of them as parame </table> <h3 id="spliting-skewed-shuffle-partitions">Spliting skewed shuffle partitions</h3> -<table class="table table-striped"> +<table> <thead><tr><th>Property Name</th><th>Default</th><th>Meaning</th><th>Since Version</th></tr></thead> <tr> <td><code>spark.sql.adaptive.optimizeSkewsInRebalancePartitions.enabled</code></td> @@ -591,7 +591,7 @@ hint has an initial partition number, columns, or both/neither of them as parame <h3 id="converting-sort-merge-join-to-broadcast-join">Converting sort-merge join to broadcast join</h3> <p>AQE converts sort-merge join to broadcast hash join when the runtime statistics of any join side is smaller than the adaptive broadcast hash join threshold. This is not as efficient as planning a broadcast hash join in the first place, but it’s better than keep doing the sort-merge join, as we can save the sorting of both the join sides, and read shuffle files locally to save network traffic(if <code class="language-plaintext highlighter-rouge">spark.sql.adaptive.localShuffleRea [...] -<table class="table table-striped"> +<table> <thead><tr><th>Property Name</th><th>Default</th><th>Meaning</th><th>Since Version</th></tr></thead> <tr> <td><code>spark.sql.adaptive.autoBroadcastJoinThreshold</code></td> @@ -613,7 +613,7 @@ hint has an initial partition number, columns, or both/neither of them as parame <h3 id="converting-sort-merge-join-to-shuffled-hash-join">Converting sort-merge join to shuffled hash join</h3> <p>AQE converts sort-merge join to shuffled hash join when all post shuffle partitions are smaller than a threshold, the max threshold can see the config <code class="language-plaintext highlighter-rouge">spark.sql.adaptive.maxShuffledHashJoinLocalMapThreshold</code>.</p> -<table class="table table-striped"> +<table> <thead><tr><th>Property Name</th><th>Default</th><th>Meaning</th><th>Since Version</th></tr></thead> <tr> <td><code>spark.sql.adaptive.maxShuffledHashJoinLocalMapThreshold</code></td> @@ -627,7 +627,7 @@ hint has an initial partition number, columns, or both/neither of them as parame <h3 id="optimizing-skew-join">Optimizing Skew Join</h3> <p>Data skew can severely downgrade the performance of join queries. This feature dynamically handles skew in sort-merge join by splitting (and replicating if needed) skewed tasks into roughly evenly sized tasks. It takes effect when both <code class="language-plaintext highlighter-rouge">spark.sql.adaptive.enabled</code> and <code class="language-plaintext highlighter-rouge">spark.sql.adaptive.skewJoin.enabled</code> configurations are enabled.</p> -<table class="table table-striped"> +<table> <thead><tr><th>Property Name</th><th>Default</th><th>Meaning</th><th>Since Version</th></tr></thead> <tr> <td><code>spark.sql.adaptive.skewJoin.enabled</code></td> @@ -664,7 +664,7 @@ hint has an initial partition number, columns, or both/neither of them as parame </table> <h3 id="misc">Misc</h3> -<table class="table table-striped"> +<table> <thead><tr><th>Property Name</th><th>Default</th><th>Meaning</th><th>Since Version</th></tr></thead> <tr> <td><code>spark.sql.adaptive.optimizer.excludedRules</code></td> diff --git a/site/docs/3.5.0/storage-openstack-swift.html b/site/docs/3.5.0/storage-openstack-swift.html index dd85b98802..d6c96bfa60 100644 --- a/site/docs/3.5.0/storage-openstack-swift.html +++ b/site/docs/3.5.0/storage-openstack-swift.html @@ -178,7 +178,7 @@ required by Keystone.</p> <p>The following table contains a list of Keystone mandatory parameters. <code>PROVIDER</code> can be any (alphanumeric) name.</p> -<table class="table table-striped"> +<table> <thead><tr><th>Property Name</th><th>Meaning</th><th>Required</th></tr></thead> <tr> <td><code>fs.swift.service.PROVIDER.auth.url</code></td> diff --git a/site/docs/3.5.0/streaming-custom-receivers.html b/site/docs/3.5.0/streaming-custom-receivers.html index 71cc9325a7..fd2b4b98fc 100644 --- a/site/docs/3.5.0/streaming-custom-receivers.html +++ b/site/docs/3.5.0/streaming-custom-receivers.html @@ -357,7 +357,7 @@ interval in the <a href="streaming-programming-guide.html">Spark Streaming Progr <p>The following table summarizes the characteristics of both types of receivers</p> -<table class="table table-striped"> +<table> <thead> <tr> <th>Receiver Type</th> diff --git a/site/docs/3.5.0/streaming-programming-guide.html b/site/docs/3.5.0/streaming-programming-guide.html index d139fae8a0..247c09c297 100644 --- a/site/docs/3.5.0/streaming-programming-guide.html +++ b/site/docs/3.5.0/streaming-programming-guide.html @@ -541,7 +541,7 @@ Streaming core artifact <code class="language-plaintext highlighter-rouge">spark-streaming-xyz_2.12</code> to the dependencies. For example, some of the common ones are as follows.</p> -<table class="table table-striped"> +<table> <thead><tr><th>Source</th><th>Artifact</th></tr></thead> <tr><td> Kafka </td><td> spark-streaming-kafka-0-10_2.12 </td></tr> <tr><td> Kinesis<br /></td><td>spark-streaming-kinesis-asl_2.12 [Amazon Software License] </td></tr> @@ -916,7 +916,7 @@ that no data will be lost due to any kind of failure. This leads to two kinds of DStreams support many of the transformations available on normal Spark RDD’s. Some of the common ones are as follows.</p> -<table class="table table-striped"> +<table> <thead><tr><th style="width:25%">Transformation</th><th>Meaning</th></tr></thead> <tr> <td> <b>map</b>(<i>func</i>) </td> @@ -1179,7 +1179,7 @@ operation <code class="language-plaintext highlighter-rouge">reduceByKeyAndWindo <p>Some of the common window operations are as follows. All of these operations take the said two parameters - <i>windowLength</i> and <i>slideInterval</i>.</p> -<table class="table table-striped"> +<table> <thead><tr><th style="width:25%">Transformation</th><th>Meaning</th></tr></thead> <tr> <td> <b>window</b>(<i>windowLength</i>, <i>slideInterval</i>) </td> @@ -1347,7 +1347,7 @@ Since the output operations actually allow the transformed data to be consumed b they trigger the actual execution of all the DStream transformations (similar to actions for RDDs). Currently, the following output operations are defined:</p> -<table class="table table-striped"> +<table> <thead><tr><th style="width:30%">Output Operation</th><th>Meaning</th></tr></thead> <tr> <td> <b>print</b>()</td> @@ -2595,7 +2595,7 @@ enabled</a> and reliable receivers, there is zero data loss. In terms of semanti <p>The following table summarizes the semantics under failures:</p> -<table class="table table-striped"> +<table> <thead> <tr> <th style="width:30%">Deployment Scenario</th> diff --git a/site/docs/3.5.0/structured-streaming-kafka-integration.html b/site/docs/3.5.0/structured-streaming-kafka-integration.html index 46e017361f..21f4e4c0bc 100644 --- a/site/docs/3.5.0/structured-streaming-kafka-integration.html +++ b/site/docs/3.5.0/structured-streaming-kafka-integration.html @@ -408,7 +408,7 @@ you can create a Dataset/DataFrame for a defined range of offsets.</p> </div> <p>Each row in the source has the following schema:</p> -<table class="table table-striped"> +<table> <thead><tr><th>Column</th><th>Type</th></tr></thead> <tr> <td>key</td> @@ -447,7 +447,7 @@ you can create a Dataset/DataFrame for a defined range of offsets.</p> <p>The following options must be set for the Kafka source for both batch and streaming queries.</p> -<table class="table table-striped"> +<table> <thead><tr><th>Option</th><th>value</th><th>meaning</th></tr></thead> <tr> <td>assign</td> @@ -479,7 +479,7 @@ for both batch and streaming queries.</p> <p>The following configurations are optional:</p> -<table class="table table-striped"> +<table> <thead><tr><th>Option</th><th>value</th><th>default</th><th>query type</th><th>meaning</th></tr></thead> <tr> <td>startingTimestamp</td> @@ -724,7 +724,7 @@ Because of this, Spark pools Kafka consumers on executors, by leveraging Apache <p>The following properties are available to configure the consumer pool:</p> -<table class="table table-striped"> +<table> <thead><tr><th>Property Name</th><th>Default</th><th>Meaning</th><th>Since Version</th></tr></thead> <tr> <td>spark.kafka.consumer.cache.capacity</td> @@ -774,7 +774,7 @@ Note that it doesn’t leverage Apache Commons Pool due to the difference of <p>The following properties are available to configure the fetched data pool:</p> -<table class="table table-striped"> +<table> <thead><tr><th>Property Name</th><th>Default</th><th>Meaning</th><th>Since Version</th></tr></thead> <tr> <td>spark.kafka.consumer.fetchedData.cache.timeout</td> @@ -802,7 +802,7 @@ solution to remove duplicates when reading the written data could be to introduc that can be used to perform de-duplication when reading.</p> <p>The Dataframe being written to Kafka should have the following columns in schema:</p> -<table class="table table-striped"> +<table> <thead><tr><th>Column</th><th>Type</th></tr></thead> <tr> <td>key (optional)</td> @@ -841,7 +841,7 @@ will be used.</p> <p>The following options must be set for the Kafka sink for both batch and streaming queries.</p> -<table class="table table-striped"> +<table> <thead><tr><th>Option</th><th>value</th><th>meaning</th></tr></thead> <tr> <td>kafka.bootstrap.servers</td> @@ -852,7 +852,7 @@ for both batch and streaming queries.</p> <p>The following configurations are optional:</p> -<table class="table table-striped"> +<table> <thead><tr><th>Option</th><th>value</th><th>default</th><th>query type</th><th>meaning</th></tr></thead> <tr> <td>topic</td> @@ -1018,7 +1018,7 @@ It will use different Kafka producer when delegation token is renewed; Kafka pro <p>The following properties are available to configure the producer pool:</p> -<table class="table table-striped"> +<table> <thead><tr><th>Property Name</th><th>Default</th><th>Meaning</th><th>Since Version</th></tr></thead> <tr> <td>spark.kafka.producer.cache.timeout</td> @@ -1161,7 +1161,7 @@ must match with Kafka broker configuration.</p> <p>Delegation tokens can be obtained from multiple clusters and <code>${cluster}</code> is an arbitrary unique identifier which helps to group different configurations.</p> -<table class="table table-striped"> +<table> <thead><tr><th>Property Name</th><th>Default</th><th>Meaning</th><th>Since Version</th></tr></thead> <tr> <td><code>spark.kafka.clusters.${cluster}.auth.bootstrap.servers</code></td> diff --git a/site/docs/3.5.0/structured-streaming-programming-guide.html b/site/docs/3.5.0/structured-streaming-programming-guide.html index d23eee64dd..a0dc13d805 100644 --- a/site/docs/3.5.0/structured-streaming-programming-guide.html +++ b/site/docs/3.5.0/structured-streaming-programming-guide.html @@ -737,7 +737,7 @@ checkpointed offsets after a failure. See the earlier section on <a href="#fault-tolerance-semantics">fault-tolerance semantics</a>. Here are the details of all the sources in Spark.</p> -<table class="table table-striped"> +<table> <thead> <tr> <th>Source</th> @@ -1953,7 +1953,7 @@ regarding watermark delays and whether data will be dropped or not.</p> <h5 id="support-matrix-for-joins-in-streaming-queries">Support matrix for joins in streaming queries</h5> -<table class="table table-striped"> +<table> <thead> <tr> <th>Left Input</th> @@ -2427,7 +2427,7 @@ to <code class="language-plaintext highlighter-rouge">org.apache.spark.sql.execu <p>Here are the configs regarding to RocksDB instance of the state store provider:</p> -<table class="table table-striped"> +<table> <thead> <tr> <th>Config Name</th> @@ -2610,7 +2610,7 @@ More information to be added in future releases.</p> <p>Different types of streaming queries support different output modes. Here is the compatibility matrix.</p> -<table class="table table-striped"> +<table> <thead> <tr> <th>Query Type</th> @@ -2748,7 +2748,7 @@ meant for debugging purposes only. See the earlier section on <a href="#fault-tolerance-semantics">fault-tolerance semantics</a>. Here are the details of all the sinks in Spark.</p> -<table class="table table-striped"> +<table> <thead> <tr> <th>Sink</th> @@ -3334,7 +3334,7 @@ If you need deduplication on output, try out <code class="language-plaintext hig the query is going to be executed as micro-batch query with a fixed batch interval or as a continuous processing query. Here are the different kinds of triggers that are supported.</p> -<table class="table table-striped"> +<table> <thead> <tr> <th>Trigger Type</th> diff --git a/site/docs/3.5.0/submitting-applications.html b/site/docs/3.5.0/submitting-applications.html index 3af859f084..400c5dc3d4 100644 --- a/site/docs/3.5.0/submitting-applications.html +++ b/site/docs/3.5.0/submitting-applications.html @@ -277,7 +277,7 @@ run it with <code class="language-plaintext highlighter-rouge">--help</code>. He <p>The master URL passed to Spark can be in one of the following formats:</p> -<table class="table table-striped"> +<table> <thead><tr><th>Master URL</th><th>Meaning</th></tr></thead> <tr><td> <code>local</code> </td><td> Run Spark locally with one worker thread (i.e. no parallelism at all). </td></tr> <tr><td> <code>local[K]</code> </td><td> Run Spark locally with K worker threads (ideally, set this to the number of cores on your machine). </td></tr> diff --git a/site/docs/3.5.0/web-ui.html b/site/docs/3.5.0/web-ui.html index 1686a1120e..e43c1104b8 100644 --- a/site/docs/3.5.0/web-ui.html +++ b/site/docs/3.5.0/web-ui.html @@ -494,7 +494,7 @@ operator shows the number of bytes written by a shuffle.</p> <p>Here is the list of SQL metrics:</p> -<table class="table table-striped"> +<table> <thead><tr><th>SQL metrics</th><th>Meaning</th><th>Operators</th></tr></thead> <tr><td> <code>number of output rows</code> </td><td> the number of output rows of the operator </td><td> Aggregate operators, Join operators, Sample, Range, Scan operators, Filter, etc.</td></tr> <tr><td> <code>data size</code> </td><td> the size of broadcast/shuffled/collected data of the operator </td><td> BroadcastExchange, ShuffleExchange, Subquery </td></tr> --------------------------------------------------------------------- To unsubscribe, e-mail: commits-unsubscr...@spark.apache.org For additional commands, e-mail: commits-h...@spark.apache.org