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| author | Andy Konwinski <andyk@berkeley.edu> | 2013-03-13 02:23:44 -0700 |
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| committer | Andy Konwinski <andyk@berkeley.edu> | 2013-03-13 02:23:44 -0700 |
| commit | cf73fbd3054737d9f82fc0af9dc7f2667b37a4a0 (patch) | |
| tree | 3cce49199738e5c0192695f514a61efcfe774350 /docs/quick-start.md | |
| parent | b63109763ba695725f8fd2d4078c2ff6e2134d19 (diff) | |
| download | spark-cf73fbd3054737d9f82fc0af9dc7f2667b37a4a0.tar.gz spark-cf73fbd3054737d9f82fc0af9dc7f2667b37a4a0.tar.bz2 spark-cf73fbd3054737d9f82fc0af9dc7f2667b37a4a0.zip | |
Fix another broken link in quick start.
Diffstat (limited to 'docs/quick-start.md')
| -rw-r--r-- | docs/quick-start.md | 2 |
1 files changed, 1 insertions, 1 deletions
diff --git a/docs/quick-start.md b/docs/quick-start.md index de304cdaff..216f7c9cc5 100644 --- a/docs/quick-start.md +++ b/docs/quick-start.md @@ -265,7 +265,7 @@ print "Lines with a: %i, lines with b: %i" % (numAs, numBs) This job simply counts the number of lines containing 'a' and the number containing 'b' in a system log file. Like in the Scala and Java examples, we use a SparkContext to create RDDs. We can pass Python functions to Spark, which are automatically serialized along with any variables that they reference. -For jobs that use custom classes or third-party libraries, we can add those code dependencies to SparkContext to ensure that they will be available on remote machines; this is described in more detail in the [Python programming guide](python-programming-guide). +For jobs that use custom classes or third-party libraries, we can add those code dependencies to SparkContext to ensure that they will be available on remote machines; this is described in more detail in the [Python programming guide](python-programming-guide.html). `SimpleJob` is simple enough that we do not need to specify any code dependencies. We can run this job using the `pyspark` script: |